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The fastMRI brain and knee dataset has enabled significant advances in exploring reconstruction methods for improving speed and image quality for Magnetic Resonance Imaging (MRI) via novel, clinically relevant reconstruction approaches. In…

Breast cancer is a highly heterogeneous disease with diverse molecular profiles. The PAM50 gene signature is widely recognized as a standard for classifying breast cancer into intrinsic subtypes, enabling more personalized treatment…

Oral cancer ranks among the most prevalent cancers globally, with a particularly high mortality rate in regions lacking adequate healthcare access. Early diagnosis is crucial for reducing mortality; however, challenges persist due to…

计算机视觉与模式识别 · 计算机科学 2025-10-03 Akshay Bhagwan Sonawane , Lena D. Swamikannan , Lakshman Tamil

Cancer is a leading cause of death in many countries. An early diagnosis of cancer based on biomedical imaging ensures effective treatment and a better prognosis. However, biomedical imaging presents challenges to both clinical institutions…

计算机视觉与模式识别 · 计算机科学 2023-01-24 Hosein Barzekar , Yash Patel , Ling Tong , Zeyun Yu

Domain generalizable model is attracting increasing attention in medical image analysis since data is commonly acquired from different institutes with various imaging protocols and scanners. To tackle this challenging domain generalization…

图像与视频处理 · 电气工程与系统科学 2021-09-21 Ran Gu , Jingyang Zhang , Rui Huang , Wenhui Lei , Guotai Wang , Shaoting Zhang

Objective: To develop and evaluate a deep radiomics model for clinically significant prostate cancer (csPCa, grade group >= 2) detection and compare its performance to Prostate Imaging Reporting and Data System (PI-RADS) assessment in a…

图像与视频处理 · 电气工程与系统科学 2024-10-22 G. A. Nketiah , M. R. Sunoqrot , E. Sandsmark , S. Langørgen , K. M. Selnæs , H. Bertilsson , M. Elschot , T. F. Bathen

Bi-parametric magnetic resonance imaging (bpMRI) has become a pivotal modality in the detection and diagnosis of clinically significant prostate cancer (csPCa). Developing AI-based systems to identify csPCa using bpMRI can transform PCa…

图像与视频处理 · 电气工程与系统科学 2024-09-24 Yuan Yuan , Euijoon Ahn , Dagan Feng , Mohamad Khadra , Jinman Kim

Dose escalation radiotherapy allows increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL), motivating the development of automated methods for fast, accurate, and consistent segmentation of PCa…

图像与视频处理 · 电气工程与系统科学 2023-03-08 Josiah Simeth , Jue Jiang , Anton Nosov , Andreas Wibmer , Michael Zelefsky , Neelam Tyagi , Harini Veeraraghavan

Magnetic resonance imaging (MRI) has become a crucial tool in the diagnosis and staging of prostate cancer, owing to its superior tissue contrast. However, it also creates large volumes of data that must be assessed by trained experts, a…

图像与视频处理 · 电气工程与系统科学 2024-06-25 Asmail Muftah , S M Schirmer , Frank C Langbein

Prostate cancer is the most prevalent cancer among men in Western countries, with 1.1 million new diagnoses every year. The gold standard for the diagnosis of prostate cancer is a pathologists' evaluation of prostate tissue. To potentially…

图像与视频处理 · 电气工程与系统科学 2020-10-23 Hans Pinckaers , Wouter Bulten , Jeroen van der Laak , Geert Litjens

Histopathological images are widely used for the analysis of diseased (tumor) tissues and patient treatment selection. While the majority of microscopy image processing was previously done manually by pathologists, recent advances in…

图像与视频处理 · 电气工程与系统科学 2024-07-12 Andrey Ignatov , Josephine Yates , Valentina Boeva

Deep learning has demonstrated remarkable performance across various tasks in medical imaging. However, these approaches primarily focus on supervised learning, assuming that the training and testing data are drawn from the same…

图像与视频处理 · 电气工程与系统科学 2023-08-03 Suruchi Kumari , Pravendra Singh

Radiotherapy treatment for prostate cancer relies on computed tomography (CT) and/or magnetic resonance imaging (MRI) for segmentation of target volumes and organs at risk (OARs). Manual segmentation of these volumes is regarded as the gold…

The accurate diagnosis of pathological subtypes of lung cancer is of paramount importance for follow-up treatments and prognosis managements. Assessment methods utilizing deep learning technologies have introduced novel approaches for…

图像与视频处理 · 电气工程与系统科学 2024-07-19 Yuan Jin , Gege Ma , Geng Chen , Tianling Lyu , Jan Egger , Junhui Lyu , Shaoting Zhang , Wentao Zhu

The clinical integration of deep learning models for brain tumor diagnosis in neuro-oncology is severely constrained by limited expert-annotated MRI data and substantial inter-institutional domain shift arising from variations in scanners,…

计算机视觉与模式识别 · 计算机科学 2026-05-06 Sapna Sachan , Amulya Kumar Mahto , Prashant Wagambar Patil

Purpose: Medical foundation models (FMs) offer a path to build high-performance diagnostic systems. However, their application to prostate cancer (PCa) detection from micro-ultrasound ({\mu}US) remains untested in clinical settings. We…

Early detection of many life-threatening diseases (e.g., prostate and breast cancer) within at-risk population can improve clinical outcomes and reduce cost of care. While numerous disease-specific "screening" tests that are closer to…

Breast cancer is one of the most common and dangerous cancers in women, while it can also afflict men. Breast cancer treatment and detection are greatly aided by the use of histopathological images since they contain sufficient phenotypic…

图像与视频处理 · 电气工程与系统科学 2023-04-12 Md Ishtyaq Mahmud , Muntasir Mamun , Ahmed Abdelgawad

Thyroid cancer is currently the fifth most common malignancy diagnosed in women. Since differentiation of cancer sub-types is important for treatment and current, manual methods are time consuming and subjective, automatic computer-aided…

Pathology foundation models (PFMs) have emerged as powerful pretrained encoders for computational pathology, but their robustness under clinically relevant distribution shifts remains insufficiently understood. We benchmark the robustness…

图像与视频处理 · 电气工程与系统科学 2026-04-29 Fredrik K. Gustafsson , Mattias Rantalainen