AIMC Topic: Prostate

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Multichannel Contribution Aware Network for Prostate Cancer Grading in Histopathology Images.

Journal of computational biology : a journal of computational molecular cell biology
Gleason grading of prostate histopathology images is widely used by pathologists for diagnosis and prognosis. Spatial characteristics of cell and tissues through staining images is essential for accurate grading of prostate cancer. Although considera...

Multidisciplinary Consensus Prostate Contours on Magnetic Resonance Imaging: Educational Atlas and Reference Standard for Artificial Intelligence Benchmarking.

International journal of radiation oncology, biology, physics
PURPOSE: Evaluation of artificial intelligence (AI) algorithms for prostate segmentation is challenging because ground truth is lacking. We aimed to: (1) create a reference standard data set with precise prostate contours by expert consensus, and (2)...

Toward a Refined PI-RADS: The Feasibility and Limitations of More Informative Metrics in Reviewing MRI Scans.

Journal of magnetic resonance imaging : JMRI
The Prostate Imaging-Reporting and Data System (PI-RADS) is a widely-adopted framework for assessing prostate cancer risk using multiparametric MRI. However, as advancements in imaging and data analytics emerge, PI-RADS faces pressure to integrate no...

Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study.

Journal of the Egyptian National Cancer Institute
BACKGROUND: Machine learning (ML) is a significant area of artificial intelligence, which can improve the accuracy of predictive or diagnostic models for differentiating between prostate biopsy outcomes. This study aims to develop a novel decision-su...

Development of Artificial Intelligence-based Real-time Automatic Fusion of Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasonography of the Prostate.

Urology
OBJECTIVE: To report the development of artificial intelligence (AI)-based software to allow for the autonomous fusion of transrectal ultrasound and multiparametric magnetic resonance images of the prostate to be used during transperineal prostate bi...

Enhanced ISUP grade prediction in prostate cancer using multi-center radiomics data.

Abdominal radiology (New York)
BACKGROUND: To explore the predictive value of radiomics features extracted from anatomical ROIs in differentiating the International Society of Urological Pathology (ISUP) grading in prostate cancer patients.

Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

IEEE journal of biomedical and health informatics
Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrectal ultrasound imaging, as a more affordable and non-invasive alternative, faces the challenge of high inter-class similarity and intra-class variabil...

Incorporating indirect MRI information in a CT-based deep learning model for prostate auto-segmentation.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Computed tomography (CT) imaging poses challenges for delineation of soft tissue structures for prostate cancer external beam radiotherapy. Guidelines require the input of magnetic resonance imaging (MRI) information. We devel...