AIMC Topic: Prostate

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Label-free histological identification of intraductal carcinoma of the prostate using texture analysis-based multimodal stimulated Raman scattering microscopy.

Scientific reports
Intraductal carcinoma of the prostate (IDC-P) is a very aggressive histopathological subtype of prostate cancer (PCa) that is strongly associated with poor clinical outcomes but for which no accurate biomarkers exist. Here, we demonstrate a novel app...

Automated Multimodal Image Registration for Prostate Cancer Using Squeeze-and-Excitation ResNet with Thin Plate Spline Transformation: A Deep Learning Approach.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Accurate spatial correlation between preoperative prostate MRI and post-prostatectomy histopathology is critical for improving prostate cancer diagnosis, treatment planning, and MRI interpretation. Current manual registration methods are t...

A modified deep learning approach for seminal vesicle region localization in prostate MRI.

Scientific reports
The seminal vesicle region plays a crucial role in male reproductive health, and its accurate evaluation is essential for diagnosing infertility and carcinoma. Magnetic resonance imaging (MRI) is the primary modality for assessment; however, manual e...

Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer.

Nature communications
The aggressiveness of prostate cancer is primarily assessed from histopathological data using the Gleason scoring system. Conventional artificial intelligence (AI) approaches can predict Gleason scores, but often lack explainability, which may limit ...

Automating prostate volume acquisition using abdominal ultrasound scans for prostate-specific antigen density calculations.

Scientific reports
Proposed methods for prostate cancer screening are currently prohibitively expensive (due to the high costs of imaging equipment such as magnetic resonance imaging and traditional ultrasound systems), inadequate in their detection rates, require high...

Detection and score grading for prostate adenocarcinoma using semantic segmentation.

PloS one
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...

Dedicated prostate DOI-TOF-PET based on the ProVision detection concept.

Physics in medicine and biology
The ProVision scanner is a dedicated prostate positron emission tomography (PET) system with limited angular coverage; it employs a new detector technology that provides high spatial resolution as well as information about depth-of-interaction (DOI) ...

Deep learning model for predicting extraprostatic extension of prostate cancer based on H&E-stained biopsy digital images.

Annals of medicine
BACKGROUND: To develop and validate a deep learning pipeline using prostate biopsy H&E slides to predict extraprostatic extension (EPE) in prostate cancer (PCa) patients.

Discovery of tumour indicating morphological changes in benign prostate biopsies through AI.

Scientific reports
Diagnostic needle biopsies that miss clinically significant prostate cancer (PCa) often sample benign tissue near hidden cancers. Such benign samples might still display subtle morphological signs of cancer elsewhere in the prostate. This study exami...

Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol.

BMJ open
INTRODUCTION: Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, ...