OBJECTIVES: To train and evaluate the performance of a machine learning triaging tool that identifies MRI negative for clinically significant prostate cancer and to compare this against non-MRI models.
PURPOSE: A critical limitation to deployment and utilization of Artificial Intelligence (AI) algorithms in radiology practice is the actual integration of algorithms directly into the clinical Picture Archiving and Communications Systems (PACS). Here...
Diagnostic and interventional radiology (Ankara, Turkey)
Nov 6, 2025
PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).
UNLABELLED: Bone metastasis (BM) is a leading cause of morbidity and mortality in patients with prostate and renal cancer. The complex and dynamic biological processes driving its progression present significant challenges for both understanding and ...
IEEE transactions on bio-medical engineering
Nov 1, 2025
Accurate segmentation of prostate tumors from multi-modal magnetic resonance (MR) images is crucial for the diagnosis and treatment of prostate cancer. However, the robustness of existing segmentation methods is limited, mainly because these methods ...
The increasing demand for point-of-care detection of low-concentration cancer biomarkers has necessitated the development of innovative nanozyme-based sensing technologies. Here, a smartphone-integrated platform is presented that utilizes artificial ...
Extrachromosomal circular DNA (eccDNA) may contribute to genomic rearrangements and tumor heterogeneity, playing a role in cancer development and progression. This study evaluates eccDNA as a biomarker for prostate cancer by characterizing its profil...
Journal of applied clinical medical physics
Sep 1, 2025
BACKGROUND: In contemporary radiation therapy, the radiation is modulated to conform the prescription dose to the tumor and spare organs at risk. The modulation results from a complex mathematical calculation that requires several iterations to reach...
Journal of applied clinical medical physics
Sep 1, 2025
BACKGROUND: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy. While methods exist to generate voxel-wise uncertainty maps from DL-based auto-segmentation models, these maps are rarely presented to clinicians.
Journal of applied clinical medical physics
Sep 1, 2025
BACKGROUND: In external beam radiation therapy (EBRT) for prostate cancer, both MRI and CT are typically used-CT provides electron density for dose calculation and visualization of bony anatomy and fiducial markers, while MRI offers superior soft tis...
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