Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation | Paper Citation Record

Observation 0ed51ebf-6d51-43ca-a9ca-0ee5c11fbd95 · outbound

This paper cites , author Hamarneh, G.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Hamarneh, G

Reference 1

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This paper cites , author Timofte, R.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Timofte, R

Reference 2

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This paper cites , author Vaidhya, K.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Vaidhya, K

Reference 3

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This paper cites Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

Reference 4

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This paper cites Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation

Reference 5

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This paper cites Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

Reference 6

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This paper cites , author Oktay, O.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Oktay, O

Reference 7

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This paper cites , author Suzuki, H.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Suzuki, H

Reference 8

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This paper cites , author Albarqouni, S.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Albarqouni, S

Reference 9

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This paper cites , author Pinckaers, H.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Pinckaers, H

Reference 10

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This paper cites , author Dubost, F.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Dubost, F

Reference 11

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Jolly, M.P

Reference 12

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This paper cites , author Lu, L.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Lu, L

Reference 13

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This paper cites Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

Reference 14

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This paper cites , author Hanna, M.G.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Hanna, M.G

Reference 15

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This paper cites , author Chaitanya, K.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Chaitanya, K

Reference 16

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This paper cites , author Karani, N.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Karani, N

Reference 17

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Joyce, T

Reference 18

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This paper cites , author Joyce, T.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Joyce, T

Reference 19

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This paper cites , author Dou, Q.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Dou, Q

Reference 20

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This paper cites Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Reference 21

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This paper cites Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation

Reference 22

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This paper cites , author Papandreou, G.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Papandreou, G

Reference 23

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Bortsova, G

Reference 24

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This paper cites An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images

Reference 25

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author de Bruijne, M

Reference 26

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This paper cites , author Elshaer, M.E.A.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Elshaer, M.E.A

Reference 27

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This paper cites , author Abdulkadir, A.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Abdulkadir, A

Reference 28

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Welling, M

Reference 29

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Liu, Y

Reference 30

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Guttag, J

Reference 31

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Kaufman, A.E

Reference 32

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Yang, G

Reference 33

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This paper cites PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation

Reference 34

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Bello, G

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Yang, J

Reference 36

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Ho, D.J

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Lee, S

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Cheng, J

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Y

Reference 40

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Y

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Ghahramani, Z

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Z

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Karssemeijer, N

Reference 44

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , year 2018

Reference 45

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Self-Supervised Similarity Learning for Digital Pathology

Reference 46

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Pouget-Abadie, J

Reference 47

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This paper cites Cost-Effective Active Learning for Melanoma Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Cost-Effective Active Learning for Melanoma Segmentation

Reference 48

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Member, S

Reference 49

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Synthetic Medical Images from Dual Generative Adversarial Networks

Reference 50

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Hoffman, J

Reference 51

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Karargyris, A

Reference 53

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Mask R-CNN

Reference 54

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Yang, G

Reference 55

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Jia, W

Reference 56

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Liu, M.Y

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This paper cites 3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation 3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation

Reference 58

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Z

Reference 59

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Z

Reference 60

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Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Belykh, E

Reference 61

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This paper cites Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

Reference 62

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Observation b2456346-c00c-4546-bfc8-bc6fea39f1d9 · outbound

This paper cites , author Kadir, T.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Kadir, T

Reference 63

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Observation 5ce98c28-b3f9-4d79-9d5a-41436d6e1db7 · outbound

This paper cites , author Huang, X.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Huang, X

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.620976Z

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Observation d3a422ab-9455-4670-81d0-a8b841f7d7af · outbound

This paper cites , author Xu, Z.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, Z

Reference 65

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Observation fe3e3d1a-2df6-41ad-8ca6-6b895aff5677 · outbound

This paper cites , author Park, S.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Park, S

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.627488Z

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Observation 1bd3511e-98dc-40d9-8906-820ba6a97388 · outbound

This paper cites , author Ledig, C.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Ledig, C

Reference 67

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Observation 602f4c8d-b142-4419-8be5-3dce69e4cf06 · outbound

This paper cites Deep learning with noisy labels: exploring techniques and remedies in medical image analysis.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Deep learning with noisy labels: exploring techniques and remedies in medical image analysis

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:46:04.298872Z

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Observation f9bbee1a-4f5a-47a2-8633-0aacd8ebb73e · outbound

This paper cites Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks

Reference 69

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Observation 044b7d72-2c8b-43ad-93fe-bd497da95a5a · outbound

This paper cites , author Gal, Y.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Gal, Y

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.638938Z

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Observation 05eac99d-63e6-4131-a9a9-73ed6859355a · outbound

This paper cites , author Bouchtiba, J.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Bouchtiba, J

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.641929Z

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Observation 2ec86c1d-4724-4c99-ab27-10ab839dfa61 · outbound

This paper cites a henb \.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation a henb \

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.644770Z

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Observation 0f842bca-f2a5-4d94-9dda-0ae58264f9f8 · outbound

This paper cites , author H \"a ne, C.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author H \"a ne, C

Reference 73

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Observation 1c5dd33a-c628-495f-aa09-7f2d4718713d · outbound

This paper cites , author Martinez, C.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Martinez, C

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.650393Z

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Observation d82b03d9-542a-4685-818a-909be2fa40e8 · outbound

This paper cites Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation

Reference 75

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:46:04.279431Z

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Observation 1d41cf4a-ec6e-49a7-a805-4e85075a451c · outbound

This paper cites , author Chen, H.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Chen, H

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.655907Z

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Observation d1d2caa0-ddf3-4294-889a-4fe6c6229b50 · outbound

This paper cites Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:46:04.267588Z

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Observation dec6bbf1-1e35-49cf-a171-4a8963c7ab17 · outbound

This paper cites , author Kamnitsas, K.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Kamnitsas, K

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.661691Z

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Observation eff3aa9a-2cfd-4552-98d0-16181180a74e · outbound

This paper cites , author Krawiec, K.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Krawiec, K

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.664546Z

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Observation 7f68bc8d-cda0-4dea-b80e-11791f63791b · outbound

This paper cites , author Kooi, T.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Kooi, T

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.667417Z

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Observation 6b2085a1-2892-483f-8ccf-80e80aea4096 · outbound

This paper cites , author Xu, D.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Xu, D

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.670246Z

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Observation 81b88906-8013-4bbe-b367-8e6da1fbe25d · outbound

This paper cites , author Ji, Z.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Ji, Z

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.672856Z

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Observation 83a4731e-1ae1-49df-9956-1b167d6f7105 · outbound

This paper cites , author Bozorgtabar, B.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Bozorgtabar, B

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.675703Z

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Observation 9508758e-5a8b-4314-af7c-60624715b6ef · outbound

This paper cites , author Sintorn, I.M.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Sintorn, I.M

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.678421Z

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Observation 1b58558c-6910-4092-9baf-f215055e9c54 · outbound

This paper cites Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images

Reference 85

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:46:04.255728Z

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Observation d21352cc-2d82-4be9-b9e1-78f6d699a46f · outbound

This paper cites , author Jakab, A.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Jakab, A

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.684338Z

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Observation 236685ed-b5eb-40a6-8f17-8145f58ef6e0 · outbound

This paper cites , author Navab, N.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Navab, N

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.687005Z

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Observation fb47836f-300c-4b02-85b7-b28800ca21bb · outbound

This paper cites A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation A Two-Stream Mutual Attention Network for Semi-supervised Biomedical Segmentation with Noisy Labels

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.689764Z

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Observation 6824f94c-b445-4130-8659-75533e65e2c8 · outbound

This paper cites , author Hamarneh, G.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Hamarneh, G

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.692995Z

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Observation 3c4b3323-772c-41af-9f34-ffe3bd041449 · outbound

This paper cites Learning to Segment Skin Lesions from Noisy Annotations.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Learning to Segment Skin Lesions from Noisy Annotations

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.695764Z

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Observation 448febf7-a0ac-43af-8ff2-7b0beb3f4d98 · outbound

This paper cites Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.698698Z

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Observation 6ff305a2-cb32-4400-bb02-a1e8400cf022 · outbound

This paper cites Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging Segmentation

Reference 92

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T10:46:04.221957Z

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Observation d97b6524-3a1b-4455-a59c-4eeeb352054e · outbound

This paper cites 3D MRI brain tumor segmentation using autoencoder regularization.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation 3D MRI brain tumor segmentation using autoencoder regularization

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.704622Z

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Observation bff7e2f7-2cf6-45f9-8193-37f8a7a40ec5 · outbound

This paper cites , author Gao, Y.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Gao, Y

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.707580Z

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Observation be8e9840-13d5-4a9a-a621-c99725805b90 · outbound

This paper cites , author Ferrante, E.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Ferrante, E

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.710452Z

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Observation 12ff0e56-56b5-454b-8b2e-30d1ef869000 · outbound

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

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Attention U-Net: Learning Where to Look for the Pancreas

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.713354Z

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Observation 63050cc1-fcac-4a66-a708-8a51bce4f6ba · outbound

This paper cites , author Peng, Z.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Peng, Z

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.716544Z

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Observation e141311f-88e6-4d98-8b31-4193a874dec8 · outbound

This paper cites , author Tiulpin, A.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Tiulpin, A

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.719315Z

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Observation 1e1d0360-e517-4ccf-81ba-52a334a16636 · outbound

This paper cites Transfer Learning with Edge Attention for Prostate MRI Segmentation.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation Transfer Learning with Edge Attention for Prostate MRI Segmentation

Reference 99

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:46:04.194678Z

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Observation 974ee8a9-a6b0-446a-a3e9-7c76678c7ba6 · outbound

This paper cites , author Doll \'a r, P.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Doll \'a r, P

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.725409Z

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Observation 74f4e74e-d7ee-4342-a553-ccd87216ef36 · outbound

This paper cites , author Venkataramani, R.

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation , author Venkataramani, R

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-14T10:46:03.728351Z

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