Renal cancer is a key reason for cancer-related deaths among males worldwide. Earlier diagnosis of renal cancer is critical since it can considerably increase the chance of survivability. However evaluating the histopathological renal tissue is a ted...
Prostate cancer remains a leading cause of mortality, necessitating precise histopathological segmentation for accurate Gleason Grade assessment. However, existing deep learning-based segmentation models lack contextual awareness and explainability, ...
Robotic-assisted radical prostatectomy (RARP) has become the gold standard treatment for localized prostate cancer. However, predicting post-operative outcomes remains challenging. This study aims to develop and validate predictive models for key out...
Prostate cancer is a major global health challenge. In this study, we present an approach for the detection and grading of prostate cancer through the semantic segmentation of adenocarcinoma tissues, specifically focusing on distinguishing between Gl...
OBJECTIVE: This study aims to develop a robust and clinically applicable framework for preoperative grading of meningiomas using T1-contrast-enhanced and T2-weighted MRI images. The approach integrates radiomic feature extraction, attention-guided de...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 11, 2025
Prostate cancer (PCa) detection and accurate grading remain critical challenges in medical diagnostics. While deep learning has shown promise in medical image analysis, existing computer-aided diagnosis approaches primarily focus on image recognition...
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 7, 2025
OBJECTIVE: Glioblastoma (GBM) is the most aggressive malignant brain tumor, associated with poor prognosis and limited therapeutic options. Accurate prognostic modeling is essential for guiding personalized treatment strategies. However, existing mod...
Differentiating pseudoprogression (PsP) from true progression (TP) in high-grade glioma (HGG) patients is still challenging and critical for effective treatment management. This meta-analysis evaluates the diagnostic accuracy of artificial intelligen...
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 4, 2025
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b...
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