A review of deep learning based methods for medical image multi-organ segmentation
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …
performance in many medical image segmentation tasks. Many deep learning-based …
Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …
medicine. This paper reviews applications of machine learning for the study of attenuation …
CBCT‐based synthetic CT generation using deep‐attention cycleGAN for pancreatic adaptive radiotherapy
Purpose Current clinical application of cone‐beam CT (CBCT) is limited to patient setup.
Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based …
Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based …
Shadow-consistent semi-supervised learning for prostate ultrasound segmentation
Prostate segmentation in transrectal ultrasound (TRUS) image is an essential prerequisite
for many prostate-related clinical procedures, which, however, is also a long-standing …
for many prostate-related clinical procedures, which, however, is also a long-standing …
Learning‐based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery
Purpose Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous
malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM …
malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM …
Deep learning in multi-organ segmentation
This paper presents a review of deep learning (DL) in multi-organ segmentation. We
summarized the latest DL-based methods for medical image segmentation and applications …
summarized the latest DL-based methods for medical image segmentation and applications …
[HTML][HTML] MicroSegNet: A deep learning approach for prostate segmentation on micro-ultrasound images
Abstract Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides
3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost …
3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost …
Advancements in Deep Learning for B-Mode Ultrasound Segmentation: A Comprehensive Review
Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US
image segmentation is crucial in image analysis. Recently, deep learning-based methods …
image segmentation is crucial in image analysis. Recently, deep learning-based methods …
MR to ultrasound image registration with segmentation‐based learning for HDR prostate brachytherapy
Purpose Propagation of contours from high‐quality magnetic resonance (MR) images to
treatment planning ultrasound (US) images with severe needle artifacts is a challenging …
treatment planning ultrasound (US) images with severe needle artifacts is a challenging …
Automated left ventricular myocardium segmentation using 3D deeply supervised attention U‐net for coronary computed tomography angiography; CT myocardium …
Purpose Segmentation of left ventricular myocardium (LVM) in coronary computed
tomography angiography (CCTA) is important for diagnosis of cardiovascular diseases. Due …
tomography angiography (CCTA) is important for diagnosis of cardiovascular diseases. Due …