Paper Citation Record · LEDGER

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.18958.

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

pith.paper-citation-record.v1
2505.18958 v2

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Pith citing papers itemized under the disclosed page cap.

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43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 00055190-3127-47e2-8fe6-fa9c7d546bc6 · outbound

This paper cites Deep learning in medical imaging and radiation therapy,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Deep learning in medical imaging and radiation therapy,

Reference 1

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Observation 3b5c5f53-bd2e-4ead-bac6-9a6172de3ba0 · outbound

This paper cites Computer-aided detection of subsolid nodules at chest ct: improved performance with deep learning–based ct section thickness reduction,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Computer-aided detection of subsolid nodules at chest ct: improved performance with deep learning–based ct section thickness reduction,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.806382Z

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Observation 7f257bf7-5640-4227-a419-9ffff5355520 · outbound

This paper cites Automated deep learning-based detection and segmentation of lung tumors at ct,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Automated deep learning-based detection and segmentation of lung tumors at ct,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.638019Z

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Observation 86da68be-3319-4096-a230-05831a1eac7d · outbound

This paper cites Crossbar-net: A novel convolutional neural network for kidney tumor segmentation in ct images,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Crossbar-net: A novel convolutional neural network for kidney tumor segmentation in ct images,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.545598Z

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Observation dc515cfc-7eb5-4a49-89ea-4603a752f568 · outbound

This paper cites Light-weight hybrid convolutional network for liver tumor segmentation.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Light-weight hybrid convolutional network for liver tumor segmentation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.400530Z

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Observation cc3091f7-9506-46cf-bba4-9abc0a07f2d1 · outbound

This paper cites Multi-scale coarse-to-fine segmentation for screening pancreatic ductal adenocarci- noma,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Multi-scale coarse-to-fine segmentation for screening pancreatic ductal adenocarci- noma,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.259303Z

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Observation 2114cff6-18d7-4f29-ac3b-ebf87ec45a18 · outbound

This paper cites Learning from partially labeled data for multi-organ and tumor segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Learning from partially labeled data for multi-organ and tumor segmentation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:37.121185Z

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Observation c3ad91b4-430d-49d2-acf8-165010644e93 · outbound

This paper cites Med3D: Transfer Learning for 3D Medical Image Analysis.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Med3D: Transfer Learning for 3D Medical Image Analysis

Reference 8

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Observation 0fd15ef0-3c40-4025-8de8-10cce3cd0fd7 · outbound

This paper cites Multi-organ segmentation over partially labeled datasets with multi-scale feature abstraction,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Multi-organ segmentation over partially labeled datasets with multi-scale feature abstraction,

Reference 9

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Observation d6ad9a68-a45c-4826-ad10-598c644419ee · outbound

This paper cites Marginal loss and exclusion loss for partially supervised multi-organ segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Marginal loss and exclusion loss for partially supervised multi-organ segmentation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.965061Z

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Observation 0b0c0846-6993-41d1-9a1e-e3ffe86f6f65 · outbound

This paper cites Dodnet: Learning to segment multi-organ and tumors from multiple partially labeled datasets,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Dodnet: Learning to segment multi-organ and tumors from multiple partially labeled datasets,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.867653Z

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Observation d6fe6e9c-d80c-4a07-b24a-d874eac0548f · outbound

This paper cites Uniseg: A prompt-driven universal segmentation model as well as a strong representation learner,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Uniseg: A prompt-driven universal segmentation model as well as a strong representation learner,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.703263Z

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Observation 4dc44b94-05c9-4546-bbda-48968766a4e5 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Learning transferable visual models from natural language supervision,

Reference 13

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Observation 7e03b020-10b4-4ca8-ae3c-9d815cecc276 · outbound

This paper cites Clip-driven universal model for organ segmentation and tumor detection,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Clip-driven universal model for organ segmentation and tumor detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.599022Z

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Observation 8647e397-4c7e-4fa2-ad81-7baaa60f4171 · outbound

This paper cites Dinov2: Learning robust visual features without supervision,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Dinov2: Learning robust visual features without supervision,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.449552Z

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Observation 97ad1524-b1fc-42ad-af3e-95170f9ce8fc · outbound

This paper cites Prior-aware neural network for partially-supervised multi-organ segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Prior-aware neural network for partially-supervised multi-organ segmentation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:36.340695Z

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Observation 1c6f40ef-0df3-40b9-be16-8b64c6fa7fcf · outbound

This paper cites Multi-structure segmentation from partially labeled datasets. application to body com- position measurements on ct scans,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Multi-structure segmentation from partially labeled datasets. application to body com- position measurements on ct scans,

Reference 17

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Observation 16a2b6ad-a876-4537-b9f9-c6e10c3a473a · outbound

This paper cites Multi-organ segmentation via co-training weight-averaged models from few-organ datasets,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Multi-organ segmentation via co-training weight-averaged models from few-organ datasets,

Reference 18

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Observation b2bc6f45-9665-462e-8030-203e5401ab17 · outbound

This paper cites Emerging properties in self-supervised vision transformers,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Emerging properties in self-supervised vision transformers,

Reference 19

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Observation b9cfe23e-9858-4f1f-a5f5-f447d60a8297 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:35.663411Z

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Observation 04f46c04-08ce-49a0-917c-98b712be7f73 · outbound

This paper cites Unsuper- vised object localization in the era of self-supervised vits: A survey,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Unsuper- vised object localization in the era of self-supervised vits: A survey,

Reference 21

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Observation fff6f4d9-8a20-4cbe-ae51-1c01c1db0073 · outbound

This paper cites Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Tokencut: Segmenting objects in images and videos with self-supervised transformer and normalized cut,

Reference 22

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Observation 7c3c0ac9-4e6f-49aa-b667-392c5a1a1b38 · outbound

This paper cites Self-supervised transformers for unsupervised object discovery using normalized cut,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Self-supervised transformers for unsupervised object discovery using normalized cut,

Reference 23

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Observation 662ba9b2-df22-474b-a274-4bde6b27a9e8 · outbound

This paper cites Cut and learn for unsupervised object detection and instance segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Cut and learn for unsupervised object detection and instance segmentation,

Reference 24

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Observation e315247f-ea19-48ef-b3bf-55da60f54d51 · outbound

This paper cites Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

Reference 25

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Observation 5fc6f9e7-5082-4ecc-adc1-df2e58fd7b17 · outbound

This paper cites Exploring scalable medical image encoders beyond text supervision,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Exploring scalable medical image encoders beyond text supervision,

Reference 26

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Observation 9122c78e-a4e6-4d0c-aaf4-73b38f9a64fa · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Xception: Deep learning with depthwise separable convolu- tions,

Reference 27

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Observation 9c9e9804-a7c2-4284-9661-09d44e6ffa5f · outbound

This paper cites Multi-modal learning from unpaired images: Application to multi-organ segmentation in ct and mri,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Multi-modal learning from unpaired images: Application to multi-organ segmentation in ct and mri,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:34.777646Z

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Observation b4d127f5-82d6-417b-a3f1-3b2186f8ceee · outbound

This paper cites The liver tumor segmentation benchmark (lits),.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation The liver tumor segmentation benchmark (lits),

Reference 29

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Observation 2aa6ac2b-d36b-402b-b043-ba1c4b174048 · outbound

This paper cites An international challenge to use artificial intelligence to define the state- of-the-art in kidney and kidney tumor segmentation in ct imaging.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation An international challenge to use artificial intelligence to define the state- of-the-art in kidney and kidney tumor segmentation in ct imaging

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:34.636733Z

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Observation 6601acc6-363b-46e3-937b-35cf1ee033c4 · outbound

This paper cites Abdomenct-1k: Is abdominal organ segmen- tation a solved problem?.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Abdomenct-1k: Is abdominal organ segmen- tation a solved problem?

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:34.484784Z

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Observation d3b24cd8-55ae-4ab4-ae41-ae079957bb01 · outbound

This paper cites Ct-org, a new dataset for multiple organ segmentation in computed tomography,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Ct-org, a new dataset for multiple organ segmentation in computed tomography,

Reference 32

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Observation 6bd613b6-7a5a-415d-bfe7-67e38daeb873 · outbound

This paper cites Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation,

Reference 33

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Observation 5efc9e24-1c59-4470-b6cf-02a651015586 · outbound

This paper cites Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge

Reference 34

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Observation cf9d50a6-8c7c-4106-a16d-d838c130d391 · outbound

This paper cites Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation,

Reference 35

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Observation 0bfe903a-f0d7-4ec7-8413-82f79fd6dab9 · outbound

This paper cites Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge,

Reference 36

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This paper cites Word: A large scale dataset, bench- mark and clinical applicable study for abdominal organ segmentation from ct image,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Word: A large scale dataset, bench- mark and clinical applicable study for abdominal organ segmentation from ct image,

Reference 37

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This paper cites The medical segmentation decathlon,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation The medical segmentation decathlon,

Reference 38

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Observation b3a50fbd-c2be-4e96-828b-121e5695cc55 · outbound

This paper cites Learn2reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Learn2reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning,

Reference 39

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Observation ab00d2a7-b28a-47cb-9548-a097190f1abb · outbound

This paper cites 3d image recon- struction for comparison of algorithm database,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation 3d image recon- struction for comparison of algorithm database,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:33.501722Z

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Observation eecb9903-a264-4370-b4c3-b8f49457ea79 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Unet++: A nested u-net architecture for medical image segmentation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:33.304316Z

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Observation 95982ae6-6513-4653-ac11-5c08bb516bbe · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 42

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Observation b108eafd-59e7-4e7a-ad0e-565cd2ee49f0 · outbound

This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,.

CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:25:33.067049Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.