AIMC Topic: Prostate
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A Novel Machine Learning-based Predictive Model of Clinically Significant Prostate Cancer and Online Risk Calculator.
Urology
Nov 12, 2024
OBJECTIVE: To create a machine-learning predictive model combining prostate imaging-reporting and data system (PI-RADS) score, PSA density, and clinical variables to predict clinically significant prostate cancer (csPCa).
Framework for Deep Learning Based Multi-Modality Image Registration of Snapshot and Pathology Images.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-modality image registration is an important task in medical imaging because it allows for information from different domains to be correlated. Histopathology plays a crucial role in oncologic surgery as it is the gold standard for investigating...
Minimizing prostate diffusion weighted MRI examination time through deep learning reconstruction.
Clinical imaging
Nov 5, 2024
PURPOSE: To study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm.
Achieving accurate prostate auto-segmentation on CT in the absence of MR imaging.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Oct 16, 2024
BACKGROUND: Magnetic resonance imaging (MRI) is considered the gold standard for prostate segmentation. Computed tomography (CT)-based segmentation is prone to observer bias, potentially overestimating the prostate volume by ∼ 30 % compared to MRI. H...
MixUNETR: A U-shaped network based on W-MSA and depth-wise convolution with channel and spatial interactions for zonal prostate segmentation in MRI.
Neural networks : the official journal of the International Neural Network Society
Oct 5, 2024
Magnetic resonance imaging (MRI) plays a pivotal role in diagnosing and staging prostate cancer. Precise delineation of the peripheral zone (PZ) and transition zone (TZ) within prostate MRI is essential for accurate diagnosis and subsequent artificia...
Histopathology-driven prostate cancer identification: A VBIR approach with CLAHE and GLCM insights.
Computers in biology and medicine
Oct 2, 2024
Efficient extraction and analysis of histopathological images are crucial for accurate medical diagnoses, particularly for prostate cancer. This research enhances histopathological image reclamation by integrating Visual-Based Image Reclamation (VBIR...
A flexible 2.5D medical image segmentation approach with in-slice and cross-slice attention.
Computers in biology and medicine
Sep 23, 2024
Deep learning has become the de facto method for medical image segmentation, with 3D segmentation models excelling in capturing complex 3D structures and 2D models offering high computational efficiency. However, segmenting 2.5D images, characterized...
Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.
Ultrasound in medicine & biology
Aug 22, 2024
OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) volume from four input ultrasound-based modalities (acoustic radiation force impulse [ARFI] imaging, shear wave elasticity imaging [SWEI], quantitative...
Robotic MR-guided high dose rate brachytherapy needle implantation in the prostate (ROBiNSon)-a proof-of-concept study.
Physics in medicine and biology
Aug 21, 2024
A robotic needle implant device for MR-guided high-dose-rate (HDR) prostate brachytherapy was developed. This study aimed to assess the feasibility and spatial accuracy of HDR brachytherapy using the robotic device, for a single intraprostatic target...
Commentary on Machine Learning to Predict Prostate Artery Embolization Outcomes? Patient Selection for Prostatic Artery Embolization: Why it Matters.
Cardiovascular and interventional radiology
Aug 19, 2024
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