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The emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), which is the most prevalent malignancy in males in the western world, enabling a better selection of…

Prostate cancer is a dominant health concern calling for advanced diagnostic tools. Utilizing digital pathology and artificial intelligence, this study explores the potential of 11 deep neural network architectures for automated Gleason…

The Gleason score is the most important prognostic marker for prostate cancer patients but suffers from significant inter-observer variability. We developed a fully automated deep learning system to grade prostate biopsies. The system was…

Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is the Gleason grading of histopathology images. The Gleason…

图像与视频处理 · 电气工程与系统科学 2022-12-27 Mohammad Mahdi Behzadi , Mohammad Madani , Hanzhang Wang , Jun Bai , Ankit Bhardwaj , Anna Tarakanova , Harold Yamase , Ga Hie Nam , Sheida Nabavi

Background: Transrectal ultrasound guided systematic biopsies of the prostate is a routine procedure to establish a prostate cancer diagnosis. However, the 10-12 prostate core biopsies only sample a relatively small volume of the prostate,…

图像与视频处理 · 电气工程与系统科学 2022-04-20 Bojing Liu , Yinxi Wang , Philippe Weitz , Johan Lindberg , Johan Hartman , Lars Egevad , Henrik Grönberg , Martin Eklund , Mattias Rantalainen

Prostate cancer (PCa) is one of the most common cancers in men around the world. The most accurate method to evaluate lesion levels of PCa is microscopic inspection of stained biopsy tissue and estimate the Gleason score of tissue…

图像与视频处理 · 电气工程与系统科学 2020-05-12 Yi-hong Zhang , Jing Zhang , Yang Song , Chaomin Shen , Guang Yang

We present a fully automated, anatomically guided deep learning pipeline for prostate cancer (PCa) risk stratification using routine MRI. The pipeline integrates three key components: an nnU-Net module for segmenting the prostate gland and…

While current research has shown the importance of Multi-parametric MRI (mpMRI) in diagnosing prostate cancer (PCa), further investigation is needed for how to incorporate the specific structures of the mpMRI data, such as the regional…

机器学习 · 统计学 2021-11-04 Jin Jin , Lin Zhang , Ethan Leng , Gregory J. Metzger , Joseph S. Koopmeiners

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

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

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…

Prostate cancer diagnosis through MR imaging have currently relied on radiologists' interpretation, whilst modern AI-based methods have been developed to detect clinically significant cancers independent of radiologists. In this study, we…

图像与视频处理 · 电气工程与系统科学 2026-01-09 Xiangcen Wu , Yipei Wang , Qianye Yang , Natasha Thorley , Shonit Punwani , Veeru Kasivisvanathan , Ester Bonmati , Yipeng Hu

Prostate cancer is one of the main diseases affecting men worldwide. The gold standard for diagnosis and prognosis is the Gleason grading system. In this process, pathologists manually analyze prostate histology slides under microscope, in…

图像与视频处理 · 电气工程与系统科学 2021-05-24 Julio Silva-Rodríguez , Adrián Colomer , Jose Dolz , Valery Naranjo

Prostate cancer (PCa) is a severe disease among men globally. It is important to identify PCa early and make a precise diagnosis for effective treatment. For PCa diagnosis, Multi-parametric magnetic resonance imaging (mpMRI) emerged as an…

图像与视频处理 · 电气工程与系统科学 2023-10-11 Anil B. Gavade , Neel Kanwal , Priyanka A. Gavade , Rajendra Nerli

Background: An increasing volume of prostate biopsies and a world-wide shortage of uro-pathologists puts a strain on pathology departments. Additionally, the high intra- and inter-observer variability in grading can result in over- and…

Advances in digital pathology and artificial intelligence (AI) offer promising opportunities for clinical decision support and enhancing diagnostic workflows. Previous studies already demonstrated AI's potential for automated Gleason…

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scoring is based on subjective microscopic examination of tumor…

Segmentation of Prostate Cancer (PCa) tissues from Gleason graded histopathology images is vital for accurate diagnosis. Although deep learning (DL) based segmentation methods achieve state-of-the-art accuracy, they rely on large datasets…

图像与视频处理 · 电气工程与系统科学 2021-10-04 Dwarikanath Mahapatra

The aggressiveness of prostate cancer, the most common cancer in men worldwide, is primarily assessed based on histopathological data using the Gleason scoring system. While artificial intelligence (AI) has shown promise in accurately…

Prostate cancer is the second most common form of cancer, though most patients have a positive prognosis with many experiencing long-term survival with current treatment options. Yet, each treatment carries varying levels of intensity and…

定量方法 · 定量生物学 2024-10-31 Jefferson Zhou , Kahn Rhrissorrakrai
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