GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI | Paper Citation Record

Observation 28aa7cf3-e089-4077-8606-2b36af25703f · outbound

This paper cites Global cancer statistics 2022: the trends projection analysis.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Global cancer statistics 2022: the trends projection analysis

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:01.138986Z

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This paper cites Cancer statistics, 2023.CA: a cancer journal for clinicians, 73(1):17–48, 2023.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Cancer statistics, 2023.CA: a cancer journal for clinicians, 73(1):17–48, 2023

Reference 2

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Observation 97abac55-7ff0-4ee2-9e56-9899db7564dd · outbound

This paper cites Development of a whole-urine, multiplexed, next-generationrna-sequencingassayforearlydetectionofaggressive prostate cancer.European urology oncology, 5(4):430–439, 2022.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Development of a whole-urine, multiplexed, next-generationrna-sequencingassayforearlydetectionofaggressive prostate cancer.European urology oncology, 5(4):430–439, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:00.743572Z

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Observation 139d233d-8a44-4aad-8812-db408286ee07 · outbound

This paper cites Prostate specific antigen densitycorrelateswithfeaturesofprostatecanceraggressiveness.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Prostate specific antigen densitycorrelateswithfeaturesofprostatecanceraggressiveness

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:00.527981Z

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Observation 0add3f22-8091-44ca-84fb-bfc33cbacef4 · outbound

This paper cites Fusion of mri to 3d trus for mechanically-assisted targeted prostate biopsy: system design and initial clinical experience.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Fusion of mri to 3d trus for mechanically-assisted targeted prostate biopsy: system design and initial clinical experience

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:00.332688Z

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Observation ff9e9b83-fe8a-453c-8d74-7fc44a0d0e39 · outbound

This paper cites Prostate zones and cancer: lost in transition?Nature Reviews Urology, 19(2):101–115, 2022.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Prostate zones and cancer: lost in transition?Nature Reviews Urology, 19(2):101–115, 2022

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:39:00.141953Z

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Observation 98be4b32-052c-4a52-b6cf-853ad74a1da4 · outbound

This paper cites Normal central zone of the prostate and central zone in- volvement by prostate cancer: clinical and mr imaging implications.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Normal central zone of the prostate and central zone in- volvement by prostate cancer: clinical and mr imaging implications

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:59.966840Z

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Observation 62dce229-8e2d-48a8-a63d-e29ccd94d11b · outbound

This paper cites Prostate tumor delineation using multiparametric magnetic resonance imag- ing:Inter-observervariabilityandpathologyvalidation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Prostate tumor delineation using multiparametric magnetic resonance imag- ing:Inter-observervariabilityandpathologyvalidation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:59.764410Z

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Observation 7d05c0ae-6c2f-4772-867c-714c428dc7a1 · outbound

This paper cites A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:59.543108Z

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Observation 1e6e805c-02ee-4818-a259-8e439fc98fc5 · outbound

This paper cites Challenge of prostate mri segmentation on t2-weighted images: inter-observer variabilityandimpactofprostatemorphology.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Challenge of prostate mri segmentation on t2-weighted images: inter-observer variabilityandimpactofprostatemorphology

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:59.353046Z

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Observation 7b0e19c3-d50d-495d-a68b-fb494a526405 · outbound

This paper cites Survey of denoising, segmentation and classification of magnetic resonance imaging for prostate cancer.Multimedia Tools and Ap- plications, 80(19):29199–29249, 2021.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Survey of denoising, segmentation and classification of magnetic resonance imaging for prostate cancer.Multimedia Tools and Ap- plications, 80(19):29199–29249, 2021

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:59.145085Z

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Observation 6839ffa2-296c-4212-a587-edafe5238315 · outbound

This paper cites A survey on cancer detection via convolutional neural networks: Current challenges and future directions.Neural Networks, 169:637–659, 2024.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A survey on cancer detection via convolutional neural networks: Current challenges and future directions.Neural Networks, 169:637–659, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:58.863647Z

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Observation a1ee14d6-a8f7-4d39-81f8-c9efab1e204e · outbound

This paper cites U-net:Convo- lutional networks for biomedical image segmentation, 2015.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI U-net:Convo- lutional networks for biomedical image segmentation, 2015

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:58.619691Z

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Observation 8c739099-7e72-4795-8e50-507749181d80 · outbound

This paper cites Saunet: Shape attentive u-net for interpretable medical image segmentation, 2020.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Saunet: Shape attentive u-net for interpretable medical image segmentation, 2020

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:58.393817Z

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Observation 02376d61-48c2-42f2-b8b5-71c91f6174db · outbound

This paper cites nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

Reference 15

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This paper cites Medical image segmentation network based on multi-scale frequency domain filter.Neural Networks, 175:106280, 2024.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Medical image segmentation network based on multi-scale frequency domain filter.Neural Networks, 175:106280, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:58.153458Z

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Observation a2568589-349b-4d68-b144-4c53e41e2cd8 · outbound

This paper cites Evolution of image segmentation using deep convolutional neural network: A survey.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Evolution of image segmentation using deep convolutional neural network: A survey

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:57.931731Z

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Observation 9162b1d7-2e2f-4b6c-b806-2433df736bed · outbound

This paper cites Deeply-supervised cnn for prostate segmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Deeply-supervised cnn for prostate segmentation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:57.737125Z

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Observation 16377443-862c-468d-a920-24e20f165b9e · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Attention U-Net: Learning Where to Look for the Pancreas

Reference 19

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Observation 5f6dd48b-64fc-4c48-9e62-aa2fcae28e64 · outbound

This paper cites A multi-scale channel attention network for prostate segmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A multi-scale channel attention network for prostate segmentation

Reference 20

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Observation 6e06e14d-d10a-4632-99f9-7d26e2b0cd30 · outbound

This paper cites Explainableaiforhealthcare: from black box to interpretable models.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Explainableaiforhealthcare: from black box to interpretable models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:57.159099Z

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Observation 6a78b507-2df1-479a-a2c5-8822e8cf1714 · outbound

This paper cites Energy andpolicyconsiderationsformoderndeeplearningresearch.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Energy andpolicyconsiderationsformoderndeeplearningresearch

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:56.893232Z

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Observation 52a1d008-dcec-44fe-b9f5-d1fccae02387 · outbound

This paper cites Green learning: Introduction, examples and outlook.Journal of Visual Communication and Image Representation, page 103685, 2022.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Green learning: Introduction, examples and outlook.Journal of Visual Communication and Image Representation, page 103685, 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:56.609938Z

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Observation ecfe335d-f7ec-478e-9c1c-979555541b7f · outbound

This paper cites Automatic segmentationoftheprostatein3dmrimagesbyatlasmatchingusing localized mutual information.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Automatic segmentationoftheprostatein3dmrimagesbyatlasmatchingusing localized mutual information

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:56.408330Z

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Observation 1f0b85b0-8402-414b-8840-0fac1bf0feea · outbound

This paper cites A multi- atlas approach for prostate segmentation in mr images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A multi- atlas approach for prostate segmentation in mr images

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:56.182487Z

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Observation 694ea46a-8d20-4bce-8772-7a233db57a02 · outbound

This paper cites Fast automatic multi-atlas segmentation of the prostate from 3d mr images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Fast automatic multi-atlas segmentation of the prostate from 3d mr images

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:56.008509Z

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Observation 2de9426a-269c-49b1-a189-47d462dc9ede · outbound

This paper cites Prostate mri segmentationusinglearnedsemanticknowledgeandgraphcuts.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Prostate mri segmentationusinglearnedsemanticknowledgeandgraphcuts

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:55.805996Z

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Observation d46a4404-96a5-4838-aea4-457b7a88bc59 · outbound

This paper cites Medical image segmentation by combining graph cuts and oriented active appearance models.IEEE transactions on image processing, 21(4):2035–2046, 2012.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Medical image segmentation by combining graph cuts and oriented active appearance models.IEEE transactions on image processing, 21(4):2035–2046, 2012

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:55.621445Z

Source-reported events for the cited work

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Observation 0c93fc53-bacb-4db2-9e1e-ce295120af1f · outbound

This paper cites Dual optimization based prostate zonal segmentation in 3d mr images.Medical image analysis, 18(4):660–673, 2014.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Dual optimization based prostate zonal segmentation in 3d mr images.Medical image analysis, 18(4):660–673, 2014

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:55.392234Z

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Observation 00173ca1-0e4a-4a3c-90f8-0cfadb1bdf94 · outbound

This paper cites Medical physics, 44(2):558–569, 2017.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Medical physics, 44(2):558–569, 2017

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:55.227262Z

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Observation 9b4f963a-2368-49c9-98a7-218a33977775 · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T21:38:45.824899Z

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Observation 3be3b9b8-f6f7-46a1-92b3-bed92cc54db8 · outbound

This paper cites Unet++: Redesigning skip connections to exploitmultiscalefeaturesinimagesegmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Unet++: Redesigning skip connections to exploitmultiscalefeaturesinimagesegmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:55.098718Z

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Observation 2fccd9ac-090b-439d-84c6-7cde768a0248 · outbound

This paper cites 3dpbv-net:anautomatedprostatemridataseg- mentationmethod.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI 3dpbv-net:anautomatedprostatemridataseg- mentationmethod

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.999603Z

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Observation 6de1e123-03d6-46bb-8faf-800b4df7e768 · outbound

This paper cites Attention-guided multi-scale learning network for automatic prostate and tumor segmentation on mri.Computers in Biology and Medicine, 165:107374, 2023.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Attention-guided multi-scale learning network for automatic prostate and tumor segmentation on mri.Computers in Biology and Medicine, 165:107374, 2023

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.899987Z

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Observation 7e8da4b4-2dbc-44f2-ab9f-dba55acdc040 · outbound

This paper cites Multiclass ensemble framework for enhanced prostate gland segmentation: Integrating self-onn decoders with efficientnet.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Multiclass ensemble framework for enhanced prostate gland segmentation: Integrating self-onn decoders with efficientnet

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.765633Z

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Observation 48c8504e-f1b7-425f-855e-ea6509e5d467 · outbound

This paper cites A two-stage cnn method for mri image segmentation of prostate with lesion.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A two-stage cnn method for mri image segmentation of prostate with lesion

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.642630Z

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Observation 8695026b-3a0b-43bf-900c-4463cd64e85b · outbound

This paper cites A dual attention-guided 3d convolution network for automatic segmentation of prostate and tumor.Biomedical Signal Processing and Control, 85:104755, 2023.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A dual attention-guided 3d convolution network for automatic segmentation of prostate and tumor.Biomedical Signal Processing and Control, 85:104755, 2023

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.543173Z

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Observation 1bcc6045-10e8-4364-9dfd-d8a89fdf91e8 · outbound

This paper cites 3dapa-net:3dadversarialpyramid anisotropic convolutional network for prostate segmentation in mr images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI 3dapa-net:3dadversarialpyramid anisotropic convolutional network for prostate segmentation in mr images

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.436018Z

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Observation da0a25a8-b5f2-4721-abec-730e517d5d62 · outbound

This paper cites Cat-net: A cross-slice attention transformer model for prostate zonal segmentation in mri.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Cat-net: A cross-slice attention transformer model for prostate zonal segmentation in mri

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.307471Z

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Observation ba11e623-4272-4c2c-97f0-75c1ffbd902b · outbound

This paper cites Semi-supervised representation learning for segmentation on medical volumes and sequences.IEEE Transactions on Medical Imaging, 2023.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Semi-supervised representation learning for segmentation on medical volumes and sequences.IEEE Transactions on Medical Imaging, 2023

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.203591Z

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Observation f9d11179-b14e-4b4f-b4ac-943acaaf66a2 · outbound

This paper cites Hd-net:hybriddiscriminativenetworkforprostatesegmentationinmr images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Hd-net:hybriddiscriminativenetworkforprostatesegmentationinmr images

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:54.097685Z

Source-reported events for the cited work

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Observation 283cc0d3-4efa-4094-8ef4-64fee3d66f71 · outbound

This paper cites Green learning: Introduction, examples and outlook.Journal of Visual Communication and Image Representation, 90:103685, 2023.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Green learning: Introduction, examples and outlook.Journal of Visual Communication and Image Representation, 90:103685, 2023

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.933856Z

Source-reported events for the cited work

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Observation 3b1eea10-e6bb-455d-9e96-562505015f91 · outbound

This paper cites Interpretable convolutional neural networks via feedforward design.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Interpretable convolutional neural networks via feedforward design

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.828607Z

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Observation 75152375-b1fd-49fd-9af0-d26f10c6333c · outbound

This paper cites In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), pages 1–5.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), pages 1–5

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.702331Z

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Observation 0cf50c69-6c10-453f-baaf-814f65e53b8a · outbound

This paper cites Voxel- hop: Successive subspace learning for als disease classification using structural mri.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Voxel- hop: Successive subspace learning for als disease classification using structural mri

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.557063Z

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Observation 3ce09a04-0df9-4336-8a24-65e57f0a8988 · outbound

This paper cites Pca-radhop:Atransparent andlightweightfeed-forwardmethodforclinicallysignificantprostate cancer segmentation.Computerized Medical Imaging and Graphics, 116:102408, 2024.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Pca-radhop:Atransparent andlightweightfeed-forwardmethodforclinicallysignificantprostate cancer segmentation.Computerized Medical Imaging and Graphics, 116:102408, 2024

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.454909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ae8acf3f-8a49-4609-82d1-8abcb1d30755 · outbound

This paper cites PSHop: A Lightweight Feed-Forward Method for 3D Prostate Gland Segmentation.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI PSHop: A Lightweight Feed-Forward Method for 3D Prostate Gland Segmentation

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-06T21:38:49.208605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 448f2d77-1414-4ad6-a63f-feef7f6cf3d0 · outbound

This paper cites Pixelhop++: A small successive-subspace-learning- based (ssl-based) model for image classification.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Pixelhop++: A small successive-subspace-learning- based (ssl-based) model for image classification

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.321476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fac8c615-0538-4f90-963c-48758e096dfc · outbound

This paper cites Enhancing edge intelligence with highly discriminant lnt features.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Enhancing edge intelligence with highly discriminant lnt features

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:53.151941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0cfef011-0853-4b56-85ab-2e07028ccc50 · outbound

This paper cites On supervised feature selection from high dimensional feature spaces.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI On supervised feature selection from high dimensional feature spaces

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:52.975661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3fc480a2-9e1f-4316-8fb1-9ce82821122e · outbound

This paper cites Xgboost: A scalable tree boosting system.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Xgboost: A scalable tree boosting system

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:52.706402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 83745b47-0159-4859-89f4-7290db26c031 · outbound

This paper cites an unresolved cited work.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:38:52.363457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 92192eaf-8a51-4036-848b-c3f8a3b57ac9 · outbound

This paper cites Evaluation of prostate segmentation algorithms for mri: the promise12 challenge.Medical image analysis, 18(2):359–373, 2014.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Evaluation of prostate segmentation algorithms for mri: the promise12 challenge.Medical image analysis, 18(2):359–373, 2014

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:52.124678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 984b1f44-f6e5-476a-a1df-ee752cf48804 · outbound

This paper cites In Graphics Gems, 1994.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI In Graphics Gems, 1994

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:51.804757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4179ffad-032f-463c-bf33-f1eac6928cfd · outbound

This paper cites Comparison and evaluation of methods for liver segmentation from ct datasets.IEEE transactions on medical imaging, 28(8):1251–1265, 2009.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Comparison and evaluation of methods for liver segmentation from ct datasets.IEEE transactions on medical imaging, 28(8):1251–1265, 2009

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:51.599317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 311685d3-1cc8-4876-903e-00ba390742c2 · outbound

This paper cites Comparing images using the hausdorff distance.IEEE Trans- actionsonpatternanalysisandmachineintelligence ,15(9):850–863, 1993.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Comparing images using the hausdorff distance.IEEE Trans- actionsonpatternanalysisandmachineintelligence ,15(9):850–863, 1993

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:51.420866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e5fcf0e-c8b5-4416-852c-0e6b0957536c · outbound

This paper cites A novel prostate segmentation method:triplefusionmodelwithhybridloss.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI A novel prostate segmentation method:triplefusionmodelwithhybridloss

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:51.236857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0f4676a1-5d77-47a9-8a99-d903129aaf8a · outbound

This paper cites Large kernel matters–improve semantic segmentation by global con- volutional network.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Large kernel matters–improve semantic segmentation by global con- volutional network

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:51.007354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ea9ebc47-7c8c-4fe1-bcc5-b0a1edc980ff · outbound

This paper cites Voxresnet: Deep voxelwise residual networks for brain segmentation from 3d mr images.NeuroImage, 170:446–455, 2018.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Voxresnet: Deep voxelwise residual networks for brain segmentation from 3d mr images.NeuroImage, 170:446–455, 2018

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:50.754735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 086e8ed5-91d6-43af-9ff5-a24a6aca194d · outbound

This paper cites 3d multi-scale discriminative network with multi- directionaledgelossforprostatezonalsegmentationinbi-parametric mr images.Neurocomputing, 418:148–161, 2020.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI 3d multi-scale discriminative network with multi- directionaledgelossforprostatezonalsegmentationinbi-parametric mr images.Neurocomputing, 418:148–161, 2020

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:50.580867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1a1b50d6-3de3-4eca-a348-85806beb7d85 · outbound

This paper cites Journal of medical imaging, 6(1):014006–014006, 2019.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Journal of medical imaging, 6(1):014006–014006, 2019

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:50.388698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 78a7f7aa-4abb-43d0-bf3c-49593e7beb27 · outbound

This paper cites Attention gated networks: Learning to leverage salient regions in medical images.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Attention gated networks: Learning to leverage salient regions in medical images

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:50.148070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e0662bee-02e0-46f6-8de1-ac9400a4c2cf · outbound

This paper cites Investigation and benchmarking of u-nets on prostate segmentation tasks.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Investigation and benchmarking of u-nets on prostate segmentation tasks

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:49.990561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f45bf6bd-a7bd-4bf0-b521-b6fda2930275 · outbound

This paper cites 3d mri brain tumor segmentation using autoen- coderregularization.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI 3d mri brain tumor segmentation using autoen- coderregularization

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:49.693484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d3c2de5a-9ad9-46cb-8554-adc19ee1d5c8 · outbound

This paper cites Prostate segmentation using z-net.

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI Prostate segmentation using z-net

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:38:49.466023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers