Paper Citation Record · LEDGER

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2607.10992.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.10992 v1

Coverage vector

measured 36 of 36 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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A source-named dated measurement, never combined with another source.

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External citation measurements

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Outbound references

Observation c18cf873-11e1-4b80-ade4-07f3953b2731 · outbound

This paper cites an unresolved cited work.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Unresolved cited work

Reference 1

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Observation abf97f59-50ec-4892-a792-9a92a34e1717 · outbound

This paper cites LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI

Reference 2

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Observation ed8391da-3f09-4e1e-8aad-7f23883f57f2 · outbound

This paper cites Dataset and Implementation We utilized contrast-enhanced, hepatobiliary-phase T1-weighted MRI volumes from Samsung Medical Center, acquired over approx- imately 10 years.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Dataset and Implementation We utilized contrast-enhanced, hepatobiliary-phase T1-weighted MRI volumes from Samsung Medical Center, acquired over approx- imately 10 years

Reference 3

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Observation b634d222-cfef-4986-b03e-b052fdd0b409 · outbound

This paper cites an unresolved cited work.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Unresolved cited work

Reference 4

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Observation 44c992c9-48ed-4373-9bf8-0d1340cc2da8 · outbound

This paper cites 2020-0-01305).

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI 2020-0-01305)

Reference 5

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Observation 010e9a0d-be02-47e5-a74c-3be770c27bfe · outbound

This paper cites Perineural invasion in cancer: a review of the literature,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Perineural invasion in cancer: a review of the literature,

Reference 6

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Observation 79b21f15-8f40-431b-a379-b2d8b5304be2 · outbound

This paper cites Perineural invasion and perineural tumor spread in head and neck cancer,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Perineural invasion and perineural tumor spread in head and neck cancer,

Reference 7

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Observation adbf0963-7cdf-4d63-af31-ed57a04b77f3 · outbound

This paper cites an unresolved cited work.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Unresolved cited work

Reference 8

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Observation a27675c6-883e-470d-9a10-aca4d2413349 · outbound

This paper cites Influence of surgical margins on overall survival after resection of intrahep- atic cholangiocarcinoma: A meta-analysis,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Influence of surgical margins on overall survival after resection of intrahep- atic cholangiocarcinoma: A meta-analysis,

Reference 9

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Observation 1d25685f-62d0-4b14-8b6e-4949f6933082 · outbound

This paper cites Perineural invasion and spread in common abdominopelvic diseases: imaging diagnosis and clinical significance,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Perineural invasion and spread in common abdominopelvic diseases: imaging diagnosis and clinical significance,

Reference 10

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Observation 08108d10-6743-48d0-9622-e1517a3ab947 · outbound

This paper cites Diagnostic accu- racy of mri in detecting the perineural spread of head and neck tumors: a systematic review and meta-analysis,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Diagnostic accu- racy of mri in detecting the perineural spread of head and neck tumors: a systematic review and meta-analysis,

Reference 11

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Observation d2f09e52-6c75-4adf-9827-93b176ab21e2 · outbound

This paper cites Zhang, W.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Zhang, W

Reference 12

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Observation 04c9d1e4-b3ff-4382-8c93-539cefb8952b · outbound

This paper cites Ct-based ra- diomics analysis for noninvasive prediction of perineural inva- sion of perihilar cholangiocarcinoma,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Ct-based ra- diomics analysis for noninvasive prediction of perineural inva- sion of perihilar cholangiocarcinoma,

Reference 13

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Observation 50e0e49e-12c6-4def-a4c8-8ccbaf672142 · outbound

This paper cites Making radiomics more reproducible across scan- ner and imaging protocol variations: a review of harmonization methods,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Making radiomics more reproducible across scan- ner and imaging protocol variations: a review of harmonization methods,

Reference 14

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Observation 8f18cf02-7bee-4a9e-8a0d-915e92cf31ce · outbound

This paper cites Reproducibil- ity and generalizability in radiomics modeling: possible strate- gies in radiologic and statistical perspectives,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Reproducibil- ity and generalizability in radiomics modeling: possible strate- gies in radiologic and statistical perspectives,

Reference 15

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Observation 584e05d6-c164-4cef-996b-d34d3bd19bef · outbound

This paper cites Enhancing radiomics reproducibility: Deep learning-based harmonization of abdominal computed tomography (ct) images,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Enhancing radiomics reproducibility: Deep learning-based harmonization of abdominal computed tomography (ct) images,

Reference 16

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Observation b552a4f4-2664-43c7-b202-ad8a1563e186 · outbound

This paper cites Deep residual learning for image recognition,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Deep residual learning for image recognition,

Reference 17

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Observation 78b49b86-764e-487d-9a34-a9ec95d740bb · outbound

This paper cites Densely connected convolutional networks,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Densely connected convolutional networks,

Reference 18

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Observation 0c5da67c-bc02-41bb-b176-2d5afcfa0b23 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Efficientnet: Rethinking model scaling for convolutional neural networks,

Reference 19

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Observation 90863102-c51f-4add-836c-de2437cd03de · outbound

This paper cites A comprehen- sive review of u-net and its variants: Advances and applica- tions in medical image segmentation,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI A comprehen- sive review of u-net and its variants: Advances and applica- tions in medical image segmentation,

Reference 20

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Observation 7c03a00d-40b2-408d-a18a-13a72edba6b7 · outbound

This paper cites Dra-net: Medical image seg- mentation based on adaptive feature extraction and region-level information fusion,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Dra-net: Medical image seg- mentation based on adaptive feature extraction and region-level information fusion,

Reference 21

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Observation 96a7de9e-0673-4ee6-b031-9be66734ecdc · outbound

This paper cites Transformers in vision: A survey,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Transformers in vision: A survey,

Reference 22

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Observation cee99304-44f6-4b43-8eae-bb81ab404ff9 · outbound

This paper cites Transformers in medical imaging: A survey,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Transformers in medical imaging: A survey,

Reference 23

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This paper cites Transforming medical imaging with transform- ers? a comparative review of key properties, current pro- gresses, and future perspectives,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Transforming medical imaging with transform- ers? a comparative review of key properties, current pro- gresses, and future perspectives,

Reference 24

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Observation 0295cea7-41d7-46c0-b8b4-147a08964684 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 25

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This paper cites Neighborhood attention transformer,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Neighborhood attention transformer,

Reference 26

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This paper cites Going deeper with convolutions,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Going deeper with convolutions,

Reference 27

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Observation fca97c88-74f3-4d5b-a5be-df2e7f468177 · outbound

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LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Aggre- gated residual transformations for deep neural networks,

Reference 28

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LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Squeeze-and-excitation net- works,

Reference 29

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This paper cites Selective kernel net- works,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Selective kernel net- works,

Reference 30

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This paper cites Xception: Deep learning with depthwise separable convolutions,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Xception: Deep learning with depthwise separable convolutions,

Reference 31

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This paper cites Mobilenetv2: Inverted residuals and linear bottle- necks,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Mobilenetv2: Inverted residuals and linear bottle- necks,

Reference 32

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This paper cites Talking-Heads Attention.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Talking-Heads Attention

Reference 33

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This paper cites Decoupled Weight Decay Regularization.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Decoupled Weight Decay Regularization

Reference 34

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LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Focal loss for dense object detection,

Reference 35

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This paper cites Grad-cam: Visual explanations from deep net- works via gradient-based localization,.

LoSA-Net: A Localized and Scale-Adaptive Network for Boundary-Sensitive Prediction of Perineural Invasion in 3D MRI Grad-cam: Visual explanations from deep net- works via gradient-based localization,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T07:49:00.628303Z

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Pith citing papers

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