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Prostate cancer (Pca) continues to be a leading cause of cancer-related mortality in men, and the limitations in precision of traditional diagnostic methods such as the Digital Rectal Exam (DRE), Prostate-Specific Antigen (PSA) testing, and…

Data augmentation (DA) is a key factor in medical image analysis, such as in prostate cancer (PCa) detection on magnetic resonance images. State-of-the-art computer-aided diagnosis systems still rely on simplistic spatial transformations to…

Prostate cancer (PCa) is the most prevalent cancer among men in the United States, accounting for nearly 300,000 cases, 29\% of all diagnoses and 35,000 total deaths in 2024. Traditional screening methods such as prostate-specific antigen…

图像与视频处理 · 电气工程与系统科学 2025-05-27 Jarett Dewbury , Chi-en Amy Tai , Alexander Wong

We consider an MRI reconstruction problem with input of k-space data at a very low undersampled rate. This can practically benefit patient due to reduced time of MRI scan, but it is also challenging since quality of reconstruction may be…

计算机视觉与模式识别 · 计算机科学 2019-04-11 Qiaoying Huang , Dong Yang , Pengxiang Wu , Hui Qu , Jingru Yi , Dimitris Metaxas

Automatic detection of brain neoplasm in Magnetic Resonance Imaging (MRI) is gaining importance in many medical diagnostic applications. This report presents two improvements for brain neoplasm detection in MRI data: an advanced…

计算机视觉与模式识别 · 计算机科学 2021-01-26 Nilanjan Sinhababu , Monalisa Sarma , Debasis Samanta

We propose a novel automatic method for accurate segmentation of the prostate in T2-weighted magnetic resonance imaging (MRI). Our method is based on convolutional neural networks (CNNs). Because of the large variability in the shape, size,…

图像与视频处理 · 电气工程与系统科学 2020-01-01 Davood Karimi , Golnoosh Samei , Yanan Shao , Septimiu Salcudean

Accurate prostate cancer diagnosis remains challenging. Even when using MRI, radiologists exhibit low specificity and significant inter-observer variability, leading to potential delays or inaccuracies in identifying clinically significant…

The detection of clinically significant prostate cancer lesions (csPCa) from biparametric magnetic resonance imaging (bp-MRI) has emerged as a noninvasive imaging technique for improving accurate diagnosis. Nevertheless, the analysis of…

计算机视觉与模式识别 · 计算机科学 2025-11-11 Mateo Ortiz , Juan Olmos , Fabio Martínez

Radiation encephalopathy (REP) is the most common complication for nasopharyngeal carcinoma (NPC) radiotherapy. It is highly desirable to assist clinicians in optimizing the NPC radiotherapy regimen to reduce radiotherapy-induced temporal…

图像与视频处理 · 电气工程与系统科学 2022-06-24 Jiansheng Fang , Anwei Li , Pu-Yun OuYang , Jiajian Li , Jingwen Wang , Hongbo Liu , Fang-Yun Xie , Jiang Liu

Early diagnosis and accurate identification of lesion location and progression in prostate cancer (PCa) are critical for assisting clinicians in formulating effective treatment strategies. However, due to the high semantic homogeneity…

图像与视频处理 · 电气工程与系统科学 2025-07-24 Zhengcheng Lin , Zuobin Ying , Zhenyu Li , Zhenyu Liu , Jian Lu , Weiping Ding

Prostate cancer (PCa) is one of the most common and aggressive cancers worldwide. The Gleason score (GS) system is the standard way of classifying prostate cancer and the most reliable method to determine the severity and treatment to…

计算机视觉与模式识别 · 计算机科学 2021-03-05 Santiago Toledo-Cortés , Diego H. Useche , Fabio A. González

The Gleason grading system using histological images is the most powerful diagnostic and prognostic predictor of prostate cancer. The current standard inspection is evaluating Gleason H&E-stained histopathology images by pathologists.…

图像与视频处理 · 电气工程与系统科学 2020-12-10 Haotian Xie , Yong Zhang , Jun Wang , Jingjing Zhang , Yifan Ma , Zhaogang Yang

Medical image distributions shift constantly due to changes in patient population and discrepancies in image acquisition. These distribution changes result in performance deterioration; deterioration that continual learning aims to…

图像与视频处理 · 电气工程与系统科学 2024-08-01 Nick Lemke , Camila González , Anirban Mukhopadhyay , Martin Mundt

We present Pre-trained Machine Reader (PMR), a novel method for retrofitting pre-trained masked language models (MLMs) to pre-trained machine reading comprehension (MRC) models without acquiring labeled data. PMR can resolve the discrepancy…

计算与语言 · 计算机科学 2023-10-17 Weiwen Xu , Xin Li , Wenxuan Zhang , Meng Zhou , Wai Lam , Luo Si , Lidong Bing

The development of accessible screening tools for early cancer detection in dogs represents a significant challenge in veterinary medicine. Routine laboratory data offer a promising, low-cost source for such tools, but their utility is…

机器学习 · 计算机科学 2025-12-11 Shumin Li

Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently, a variety of deep learning methods have achieved remarkable progress in this task, usually relying on large amounts of training data. Due…

图像与视频处理 · 电气工程与系统科学 2020-02-20 Quande Liu , Qi Dou , Lequan Yu , Pheng Ann Heng

Breast cancer, the second leading cause of cancer-related deaths globally, accounts for a quarter of all cancer cases [1]. To lower this death rate, it is crucial to detect tumors early, as early-stage detection significantly improves…

计算机视觉与模式识别 · 计算机科学 2025-09-26 Samia Saeed , Khuram Naveed

The diagnosis and segmentation of tumors using any medical diagnostic tool can be challenging due to the varying nature of this pathology. Magnetic Reso- nance Imaging (MRI) is an established diagnostic tool for various diseases and…

计算机视觉与模式识别 · 计算机科学 2017-11-01 Tanvi Gupta , Pranay Manocha , Tapan K. Gandhi , RK Gupta , BK Panigrahi

In 2020, prostate cancer saw a staggering 1.4 million new cases, resulting in over 375,000 deaths. The accurate identification of clinically significant prostate cancer is crucial for delivering effective treatment to patients.…

图像与视频处理 · 电气工程与系统科学 2024-05-14 Chi-en Amy Tai , Alexander Wong

Patient-reported outcomes (PROs) directly collected from cancer patients being treated with radiation therapy play a vital role in assisting clinicians in counseling patients regarding likely toxicities. Precise prediction and evaluation of…

机器学习 · 计算机科学 2024-11-19 Yang Yan , Zhong Chen , Cai Xu , Xinglei Shen , Jay Shiao , John Einck , Ronald C Chen , Hao Gao