医学 AI - arXivDaily 专题

2409.15092 2024-12-23 cs.CV cs.AI 79%

M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images

Hongyi Wang, Xiuju Du, Jing Liu, Shuyi Ouyang, Yen-Wei Chen, Lanfen Lin

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments Improved from our previous unpublished work arXiv:2401.10608. arXiv admin note: substantial text overlap with arXiv:2401.10608

2407.07841 2024-12-18 cs.CV 79%

Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective

Shengjia Chen, Gabriele Campanella, Abdulkadir Elmas, Aryeh Stock, Jennifer Zeng, Alexandros D. Polydorides, Adam J. Schoenfeld, Kuan-lin Huang, Jane Houldsworth, Chad Vanderbilt, Thomas J. Fuchs

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments 10 pages, 2 figures

2412.12077 2024-12-17 cs.CV 79%

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Yuxuan Sun, Yixuan Si, Chenglu Zhu, Xuan Gong, Kai Zhang, Pingyi Chen, Ye Zhang, Zhongyi Shui, Tao Lin, Lin Yang

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments 22 pages, 13 figures

2411.11613 2024-11-20 cs.CV 79%

Leveraging Computational Pathology AI for Noninvasive Optical Imaging Analysis Without Retraining

Danny Barash, Emilie Manning, Aidan Van Vleck, Omri Hirsch, Kyi Lei Aye, Jingxi Li, Philip O. Scumpia, Aydogan Ozcan, Sumaira Aasi, Kerri E. Rieger, Kavita Y. Sarin, Oren Freifeld, Yonatan Winetraub

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2411.09894 2024-11-18 cs.CV 79%

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement

Yanyan Huang, Weiqin Zhao, Yihang Chen, Yu Fu, Lequan Yu

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2408.00738 2024-11-07 cs.CV 79%

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Eric Zimmermann, Eugene Vorontsov, Julian Viret, Adam Casson, Michal Zelechowski, George Shaikovski, Neil Tenenholtz, James Hall, David Klimstra, Razik Yousfi, Thomas Fuchs, Nicolo Fusi, Siqi Liu, Kristen Severson

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2410.16038 2024-10-22 cs.CV 79%

Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios

Jeaung Lee, Jeewoo Lim, Keunho Byeon, Jin Tae Kwak

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2409.20383 2024-10-01 cs.LG cs.NA math.NA 79%

Beyond Derivative Pathology of PINNs: Variable Splitting Strategy with Convergence Analysis

Yesom Park, Changhoon Song, Myungjoo Kang

专题命中病理影像：pathology(title,abstract)；分类 cs.LG

2409.15574 2024-09-25 cs.CV 79%

Clinical-grade Multi-Organ Pathology Report Generation for Multi-scale Whole Slide Images via a Semantically Guided Medical Text Foundation Model

Jing Wei Tan, SeungKyu Kim, Eunsu Kim, Sung Hak Lee, Sangjeong Ahn, Won-Ki Jeong

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2408.15032 2024-08-28 cs.CV cs.AI 79%

Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathology

Yuqi Zhang, Xiaoqian Zhang, Jiakai Wang, Yuancheng Yang, Taiying Peng, Chao Tong

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2408.13542 2024-08-27 cs.CV 79%

Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset

Ammar Ahmed, Ali Shariq Imran, Zenun Kastrati, Sher Muhammad Daudpota, Mohib Ullah, Waheed Noord

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Journal ref Computers in Biology and Medicine, https://www.sciencedirect.com/journal/computers-in-biology-and-medicine, 2024

2408.09746 2024-08-20 cs.CV cs.AI 79%

Enhanced Cascade Prostate Cancer Classifier in mp-MRI Utilizing Recall Feedback Adaptive Loss and Prior Knowledge-Based Feature Extraction

Kun Luo, Bowen Zheng, Shidong Lv, Jie Tao, Qiang Wei

专题命中病理影像：MRI(title)；diagnosis(abstract)；分类 cs.CV

2311.17804 2024-08-05 cs.CV 79%

The Importance of Downstream Networks in Digital Pathology Foundation Models

Gustav Bredell, Marcel Fischer, Przemyslaw Szostak, Samaneh Abbasi-Sureshjani, Alvaro Gomariz

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2407.14426 2024-07-22 cs.CV 79%

Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models

Hyun-Jic Oh, Won-Ki Jeong

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments MICCAI 2024 accepted

2407.00203 2024-07-02 cs.CV 79%

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration

Yuxuan Sun, Yunlong Zhang, Yixuan Si, Chenglu Zhu, Zhongyi Shui, Kai Zhang, Jingxiong Li, Xingheng Lyu, Tao Lin, Lin Yang

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments 13 pages, 3 figures

2405.14230 2024-05-24 cs.CV cs.AI cs.CL 79%

Boosting Medical Image-based Cancer Detection via Text-guided Supervision from Reports

Guangyu Guo, Jiawen Yao, Yingda Xia, Tony C. W. Mok, Zhilin Zheng, Junwei Han, Le Lu, Dingwen Zhang, Jian Zhou, Ling Zhang

专题命中病理影像：medical image(title,abstract)；分类 cs.CV

2405.09934 2024-05-17 cs.CV cs.AI 79%

Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance

Milda Pocevičiūtė, Gabriel Eilertsen, Stina Garvin, Claes Lundström

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2405.09851 2024-05-17 eess.IV cs.CV q-bio.QM 79%

Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images -- Nevus & Melanoma

Yi Cui, Yao Li, Jayson R. Miedema, Sharon N. Edmiston, Sherif Farag, J. S. Marron, Nancy E. Thomas

专题命中病理影像：medical image(abstract)；pathology(abstract)；diagnosis(abstract)；分类 cs.CV、q-bio、eess.IV

Comments 5 figures, NeurIPS 2022 Workshop

2405.01688 2024-05-06 cs.CV 79%

Adapting Self-Supervised Learning for Computational Pathology

Eric Zimmermann, Neil Tenenholtz, James Hall, George Shaikovski, Michal Zelechowski, Adam Casson, Fausto Milletari, Julian Viret, Eugene Vorontsov, Siqi Liu, Kristen Severson

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments Presented at DCA in MI Workshop, CVPR 2024

2404.07676 2024-04-12 cs.CV cs.AI 79%

Model-based Cleaning of the QUILT-1M Pathology Dataset for Text-Conditional Image Synthesis

Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Christopher C. Kaltenecker, Christof A. Bertram

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments 4 pages (short paper)

2403.07407 2024-03-13 cs.CV 79%

In-context learning enables multimodal large language models to classify cancer pathology images

Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather

专题命中病理影像：pathology(title)；medical image(abstract)；分类 cs.CV

Comments 40 pages, 5 figures

2311.08359 2024-03-13 cs.CV 79%

Rotation-Agnostic Image Representation Learning for Digital Pathology

Saghir Alfasly, Abubakr Shafique, Peyman Nejat, Jibran Khan, Areej Alsaafin, Ghazal Alabtah, H. R. Tizhoosh

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments CVPR 2024 - 23 pages, 10 figures, and 18 tables

2403.06800 2024-03-12 cs.CV 79%

MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology

Shu Yang, Yihui Wang, Hao Chen

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments Submitted to MICCAI-2024

2401.13887 2024-01-26 cs.CL cs.LG 79%

A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification

Madhumita Sushil, Travis Zack, Divneet Mandair, Zhiwei Zheng, Ahmed Wali, Yan-Ning Yu, Yuwei Quan, Atul J. Butte

专题命中病理影像：pathology(title,abstract)；分类 cs.LG

2307.04596 2024-01-26 cs.CV 79%

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Guillaume Vray, Devavrat Tomar, Jean-Philippe Thiran, Behzad Bozorgtabar

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

Comments 13 pages

Journal ref IEEE Transactions on Medical Imaging 2024

2206.04425 2023-12-07 cs.CV 79%

Multiple Instance Learning for Digital Pathology: A Review on the State-of-the-Art, Limitations & Future Potential

Michael Gadermayr, Maximilian Tschuchnig

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2311.09902 2023-11-17 cs.CV 79%

Selection of Distinct Morphologies to Divide & Conquer Gigapixel Pathology Images

Abubakr Shafique, Saghir Alfasly, Areej Alsaafin, Peyman Nejat, Jibran A. Khan, H. R. Tizhoosh

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2211.05862 2023-10-02 cs.CV cs.AI 79%

MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis

Michael Gadermayr, Lukas Koller, Maximilian Tschuchnig, Lea Maria Stangassinger, Christina Kreutzer, Sebastien Couillard-Despres, Gertie Janneke Oostingh, Anton Hittmair

专题命中病理影像：diagnosis(title,abstract)；分类 cs.CV

Comments MICCAI'23, https://gitlab.com/mgadermayr/mixupmil

2309.06439 2023-09-13 cs.CV 79%

Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning

Saarthak Kapse, Srijan Das, Jingwei Zhang, Rajarsi R. Gupta, Joel Saltz, Dimitris Samaras, Prateek Prasanna

专题命中病理影像：pathology(title,abstract)；分类 cs.CV

2301.01931 2023-08-15 cs.CV cs.AI 79%

Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis

Bahareh Morovati, Reza Lashgari, Mojtaba Hajihasani, Hasti Shabani

专题命中病理影像：diagnosis(title,abstract)；分类 cs.CV

1. 病理影像 3457 篇

M2OST: Many-to-one Regression for Predicting Spatial Transcriptomics from Digital Pathology Images

Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective

CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology

Leveraging Computational Pathology AI for Noninvasive Optical Imaging Analysis Without Retraining

Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement

Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology

Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios

Beyond Derivative Pathology of PINNs: Variable Splitting Strategy with Convergence Analysis

Clinical-grade Multi-Organ Pathology Report Generation for Multi-scale Whole Slide Images via a Semantically Guided Medical Text Foundation Model

Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathology

Learning from the few: Fine-grained approach to pediatric wrist pathology recognition on a limited dataset

Enhanced Cascade Prostate Cancer Classifier in mp-MRI Utilizing Recall Feedback Adaptive Loss and Prior Knowledge-Based Feature Extraction

The Importance of Downstream Networks in Digital Pathology Foundation Models

Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models

PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration

Boosting Medical Image-based Cancer Detection via Text-guided Supervision from Reports

Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance

Region of Interest Detection in Melanocytic Skin Tumor Whole Slide Images -- Nevus & Melanoma

Adapting Self-Supervised Learning for Computational Pathology

Model-based Cleaning of the QUILT-1M Pathology Dataset for Text-Conditional Image Synthesis

In-context learning enables multimodal large language models to classify cancer pathology images

Rotation-Agnostic Image Representation Learning for Digital Pathology

MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology

A comparative study of zero-shot inference with large language models and supervised modeling in breast cancer pathology classification

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

Multiple Instance Learning for Digital Pathology: A Review on the State-of-the-Art, Limitations & Future Potential

Selection of Distinct Morphologies to Divide & Conquer Gigapixel Pathology Images

MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis

Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning

Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis