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Related papers: Pathologist-Level Grading of Prostate Biopsies wit…

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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.…

Image and Video Processing · Electrical Eng. & Systems 2020-12-10 Haotian Xie , Yong Zhang , Jun Wang , Jingjing Zhang , Yifan Ma , Zhaogang Yang

Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with almost 1.41 million new cases and around 375,000 deaths in 2020. Artificial Intelligence algorithms have had a huge…

Artificial Intelligence (AI) can potentially support histopathologists in the diagnosis of a broad spectrum of cancer types. In colorectal cancer (CRC), AI can alleviate the laborious task of characterization and reporting on resected…

Image and Video Processing · Electrical Eng. & Systems 2023-02-10 John-Melle Bokhorst , Iris D. Nagtegaal , Filippo Fraggetta , Simona Vatrano , Wilma Mesker , Michael Vieth , Jeroen van der Laak , Francesco Ciompi

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…

Histology-based grade classification is clinically important for many cancer types in stratifying patients distinct treatment groups. In prostate cancer, the Gleason score is a grading system used to measure the aggressiveness of prostate…

Computer Vision and Pattern Recognition · Computer Science 2019-11-07 Jingwen Wang , Richard J. Chen , Ming Y. Lu , Alexander Baras , Faisal Mahmood

The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs), leading to degraded AI performance and posing a challenge for widespread clinical…

Artificial intelligence foundation models are increasingly deployed for prostate cancer Gleason grading, where GP3/GP4 distinction directly impacts treatment decisions. However, these models may achieve high validation accuracy by learning…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Joshua L. Ebbert , Dennis Della Corte

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…

Computer Vision and Pattern Recognition · Computer Science 2021-03-05 Santiago Toledo-Cortés , Diego H. Useche , Fabio A. González

Prostate cancer is one of the main diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic tool for prostate cancer. This is obtained via the visual analysis of cancerous patterns in prostate biopsies…

Image and Video Processing · Electrical Eng. & Systems 2021-05-24 Julio Silva-Rodríguez , Adrián Colomer , Valery Naranjo

In the cancer diagnosis pipeline, digital pathology plays an instrumental role in the identification, staging, and grading of malignant areas on biopsy tissue specimens. High resolution histology images are subject to high variance in…

Image and Video Processing · Electrical Eng. & Systems 2023-08-17 Vasileios Magoulianitis , Catherine A. Alexander , C. -C. Jay Kuo

Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 million tissue patches…

Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell carcinoma and adenocarcinoma are two major subtypes of carcinoma,…

Image and Video Processing · Electrical Eng. & Systems 2022-01-20 Swathi Prabhua , Keerthana Prasada , Antonio Robels-Kelly , Xuequan Lu

Purpose of review: Artificial intelligence (AI) has become popular in medical applications, specifically as a clinical support tool for computer-aided diagnosis. These tools are typically employed on medical data (i.e., image, molecular…

Machine Learning · Computer Science 2022-06-08 Ahmad Chaddad , Yousef Katib , Lama Hassan

Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent results in the detection of prostate cancer (PCa). However, characterizing prostate lesions aggressiveness in mp-MRI sequences is impossible in clinical practice, and…

Image and Video Processing · Electrical Eng. & Systems 2022-11-28 Audrey Duran , Gaspard Dussert , Olivier Rouvière , Tristan Jaouen , Pierre-Marc Jodoin , Carole Lartizien

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…

Grading precancerous lesions on whole slide images is a challenging task: the continuous space of morphological phenotypes makes clear-cut decisions between different grades often difficult, leading to low inter- and intra-rater agreements.…

Image and Video Processing · Electrical Eng. & Systems 2023-03-09 Mélanie Lubrano , Yaëlle Bellahsen-Harrar , Rutger Fick , Cécile Badoual , Thomas Walter

Prostate cancer is one of the most frequently diagnosed malignancies in men worldwide. However, precise prediction of biochemical recurrence (BCR) after radical prostatectomy remains challenging due to the multifocality of tumors…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yesung Cho , Dongmyung Shin , Sujeong Hong , Jooyeon Lee , Seongmin Park , Geongyu Lee , Jongbae Park , Hong Koo Ha

Prostate cancer is a prevalent malignancy among men aged 50 and older. Current diagnostic methods primarily rely on blood tests, PSA:Prostate-Specific Antigen levels, and Digital Rectal Examinations (DRE). However, these methods suffer from…

Machine Learning · Computer Science 2023-09-28 Amit Mathapati

We investigate the connection between visual semantic features defined in PI-RADS and associated risk factors, moving beyond abnormal imaging findings, establishing a shared framework between medical and AI professionals by creating a…

Artificial intelligence systems show promise to aid in the di- agnostic pathway of prostate cancer (PC), by supporting radiologists in interpreting magnetic resonance images (MRI) of the prostate. Most MRI-based systems are designed to…

Image and Video Processing · Electrical Eng. & Systems 2025-02-18 Erlend Sortland Rolfsnes , Philip Thangngat , Trygve Eftestøl , Tobias Nordström , Fredrik Jäderling , Martin Eklund , Alvaro Fernandez-Quilez