Paper Citation Record · LEDGER

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI

As of 23 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2508.07815.

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

pith.paper-citation-record.v1
2508.07815 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:54:10.490234Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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verified fuzzy20
unresolved13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a11da4c9-92ba-4acc-ad4a-f09a07fc098a · outbound

This paper cites ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection

Reference 1

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Source-reported events for the cited work

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Observation 1e72a7ce-a567-41d2-9d12-2b1c080fb10b · outbound

This paper cites an unresolved cited work.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-05T21:54:15.902335Z

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Observation 6dea6cda-4d0c-48fa-9a06-4f1ba7f1cfdb · outbound

This paper cites an unresolved cited work.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Unresolved cited work

Reference 3

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Observation 68b0e152-a900-4ecb-a702-7a768c2264d7 · outbound

This paper cites an unresolved cited work.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-05T21:54:15.485664Z

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Observation 3e6243e0-d2e8-4f5c-a21e-607d05e2bd9d · outbound

This paper cites an unresolved cited work.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Unresolved cited work

Reference 5

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Observation 98fce42a-878f-43c1-96f1-7997e5b944f7 · outbound

This paper cites This superiority in capturing precise anomaly boundaries is a direct result of our architectural co-design.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI This superiority in capturing precise anomaly boundaries is a direct result of our architectural co-design

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:15.001407Z

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Observation a55fca34-3f1f-40db-8dbd-931b0946a0a5 · outbound

This paper cites an unresolved cited work.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-05T21:54:14.780953Z

Source-reported events for the cited work

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Observation b7f4d146-4182-4f2e-b3a9-3f7b1c8ee9a5 · outbound

This paper cites Flamingo: a vi- sual language model for few-shot learning,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Flamingo: a vi- sual language model for few-shot learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:14.513466Z

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Observation d4411f2b-9292-412c-a186-143dc3e06c75 · outbound

This paper cites Visual instruction tuning,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Visual instruction tuning,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:08.779493Z

Source-reported events for the cited work

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Observation ce315b2f-b85a-43f0-a265-d89590adb589 · outbound

This paper cites Learning trans- ferable visual models from natural language supervision,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Learning trans- ferable visual models from natural language supervision,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:08.866441Z

Source-reported events for the cited work

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Observation a0235539-d369-40d1-9552-1f4e98ddd7c8 · outbound

This paper cites Towards total recall in industrial anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Towards total recall in industrial anomaly detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:14.319497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation da478db2-a0e1-4c4c-9592-4ed62a55a5c9 · outbound

This paper cites Padim: a patch distribution modeling frame- work for anomaly detection and localization,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Padim: a patch distribution modeling frame- work for anomaly detection and localization,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:14.039810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8038f5de-c549-4902-b89c-f7681bb4e14d · outbound

This paper cites Winclip: Zero- /few-shot anomaly classification and segmentation,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Winclip: Zero- /few-shot anomaly classification and segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:13.847408Z

Source-reported events for the cited work

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Observation d8a02527-d952-4333-9f9b-3fbabf538cfe · outbound

This paper cites Anomalyclip: Object-agnostic prompt learn- ing for zero-shot anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Anomalyclip: Object-agnostic prompt learn- ing for zero-shot anomaly detection,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.143578Z

Source-reported events for the cited work

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Observation 4d70f291-e69c-4d35-9062-2c082d0a0c9c · outbound

This paper cites Adaclip: Adapt- ing clip with hybrid learnable prompts for zero-shot anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Adaclip: Adapt- ing clip with hybrid learnable prompts for zero-shot anomaly detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:13.711570Z

Source-reported events for the cited work

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Observation 50b0c048-d8cd-4552-8f4b-256577d2f065 · outbound

This paper cites Clip-ad: A language-guided staged dual-path model for zero- shot anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Clip-ad: A language-guided staged dual-path model for zero- shot anomaly detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:13.487548Z

Source-reported events for the cited work

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Observation 0514a760-a319-41ea-9188-2f01d783fc0b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.320282Z

Source-reported events for the cited work

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Observation b06a53e2-0f55-4393-9935-2860dd234408 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Fully convolutional networks for semantic segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:13.312138Z

Source-reported events for the cited work

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Observation 3abd406e-ffc8-466f-ae90-bab1b2ea3280 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI U-net: Convolutional networks for biomedical image segmentation,

Reference 19

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Source-reported events for the cited work

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Observation 4fe73820-679c-449d-9481-db9676a69de4 · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Parameter-efficient transfer learning for nlp,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:13.149811Z

Source-reported events for the cited work

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Observation 0bf1fbed-ffe1-403c-885f-964cbf9ac50d · outbound

This paper cites Lora: Low-rank adaptation of large language models.,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Lora: Low-rank adaptation of large language models.,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.548360Z

Source-reported events for the cited work

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Observation 2a165702-089e-40e4-9a01-3d1321337fdd · outbound

This paper cites Convolutional bypasses are better vision transformer adapters,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Convolutional bypasses are better vision transformer adapters,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:12.943885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 98ee29ae-a108-4f98-b86f-de20dfb07cb1 · outbound

This paper cites Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.686517Z

Source-reported events for the cited work

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Observation 967aa5f1-5585-420b-9e82-0580508b46ca · outbound

This paper cites Focal loss for dense object detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Focal loss for dense object detection,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T21:54:09.782781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf414e93-df84-4d64-90c1-1bfe17fa324d · outbound

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

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI V-net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:12.661580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ddd01bfd-f126-43b2-9e87-762407cd61c5 · outbound

This paper cites Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:12.397291Z

Source-reported events for the cited work

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Observation c17b6c9f-0810-4056-bf23-1666974b94d4 · outbound

This paper cites Spot-the-difference self-supervised pre- training for anomaly detection and segmentation,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Spot-the-difference self-supervised pre- training for anomaly detection and segmentation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:12.113226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2faec6f9-37d2-49e9-b01c-b7e3496071da · outbound

This paper cites Vt-adl: A vision transformer network for image anomaly detection and localization,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Vt-adl: A vision transformer network for image anomaly detection and localization,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.794535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ee4477fd-e8b9-4620-852f-60d80f4f09a3 · outbound

This paper cites Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.574334Z

Source-reported events for the cited work

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Observation 0350f1c3-c7e1-43b3-a4de-5531af4c1683 · outbound

This paper cites A coarse-to-fine model for rail surface defect detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI A coarse-to-fine model for rail surface defect detection,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.378147Z

Source-reported events for the cited work

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Observation 63a94d7d-24b2-4838-83fb-8cfec2651804 · outbound

This paper cites Bmad: Benchmarks for medical anomaly detection,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Bmad: Benchmarks for medical anomaly detection,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.253117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 89d1ada8-edab-4043-a681-f307397dcc44 · outbound

This paper cites Automated polyp detection in colonoscopy videos using shape and context information,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Automated polyp detection in colonoscopy videos using shape and context information,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.185398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4664a2c6-f125-45d5-9080-0c6d3496dd06 · outbound

This paper cites Wm- dova maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Wm- dova maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:11.092014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c8f4d3b-b6d0-4f0b-bafe-55987a2250e3 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset,.

Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI Kvasir-seg: A segmented polyp dataset,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T21:54:10.930999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.