Ultrasound prostate segmentation based on multidirectional deeply supervised V‐Net
Purpose Transrectal ultrasound (TRUS) is a versatile and real‐time imaging modality that is
commonly used in image‐guided prostate cancer interventions (eg, biopsy and …
commonly used in image‐guided prostate cancer interventions (eg, biopsy and …
Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images
N Orlando, DJ Gillies, I Gyacskov, C Romagnoli… - Medical …, 2020 - Wiley Online Library
Purpose Needle‐based procedures for diagnosing and treating prostate cancer, such as
biopsy and brachytherapy, have incorporated three‐dimensional (3D) transrectal ultrasound …
biopsy and brachytherapy, have incorporated three‐dimensional (3D) transrectal ultrasound …
Deep attentional features for prostate segmentation in ultrasound
Automatic prostate segmentation in transrectal ultrasound (TRUS) is of essential importance
for image-guided prostate biopsy and treatment planning. However, developing such …
for image-guided prostate biopsy and treatment planning. However, developing such …
Deep attentive features for prostate segmentation in 3D transrectal ultrasound
Automatic prostate segmentation in transrectal ultrasound (TRUS) images is of essential
importance for image-guided prostate interventions and treatment planning. However …
importance for image-guided prostate interventions and treatment planning. However …
H-ProMed: Ultrasound image segmentation based on the evolutionary neural network and an improved principal curve
The purpose of this work is to develop a method for accurate and robust prostate
segmentation in transrectal ultrasound (TRUS) images. These images are difficult to …
segmentation in transrectal ultrasound (TRUS) images. These images are difficult to …
H-SegMed: a hybrid method for prostate segmentation in TRUS images via improved closed principal curve and improved enhanced machine learning
Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …
registration, and patient-specific anatomical modeling for surgical planning and image …
Effect of dataset size, image quality, and image type on deep learning-based automatic prostate segmentation in 3D ultrasound
Abstract Three-dimensional (3D) transrectal ultrasound (TRUS) is utilized in prostate cancer
diagnosis and treatment, necessitating time-consuming manual prostate segmentation. We …
diagnosis and treatment, necessitating time-consuming manual prostate segmentation. We …
HF-UNet: learning hierarchically inter-task relevance in multi-task U-net for accurate prostate segmentation in CT images
Accurate segmentation of the prostate is a key step in external beam radiation therapy
treatments. In this paper, we tackle the challenging task of prostate segmentation in CT …
treatments. In this paper, we tackle the challenging task of prostate segmentation in CT …
Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images
The goal of this work was to develop a method for accurate and robust automatic
segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images …
segmentation of the prostate clinical target volume in transrectal ultrasound (TRUS) images …
Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study
Prostate biopsy and image-guided treatment procedures are often performed under the
guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion …
guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion …
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