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 …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
Deep learning empowered volume delineation of whole-body organs-at-risk for accelerated radiotherapy
In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …
Artificial intelligence in diagnostic imaging: impact on the radiography profession
The arrival of artificially intelligent systems into the domain of medical imaging has focused
attention and sparked much debate on the role and responsibilities of the radiologist …
attention and sparked much debate on the role and responsibilities of the radiologist …
Boundary-weighted domain adaptive neural network for prostate MR image segmentation
Accurate segmentation of the prostate from magnetic resonance (MR) images provides
useful information for prostate cancer diagnosis and treatment. However, automated …
useful information for prostate cancer diagnosis and treatment. However, automated …
Xbound-former: Toward cross-scale boundary modeling in transformers
Skin lesion segmentation from dermoscopy images is of great significance in the quantitative
analysis of skin cancers, which is yet challenging even for dermatologists due to the inherent …
analysis of skin cancers, which is yet challenging even for dermatologists due to the inherent …
Boundary-aware context neural network for medical image segmentation
Medical image segmentation can provide a reliable basis for further clinical analysis and
disease diagnosis. With the development of convolutional neural networks (CNNs), medical …
disease diagnosis. With the development of convolutional neural networks (CNNs), medical …
Multi-scale context-guided deep network for automated lesion segmentation with endoscopy images of gastrointestinal tract
Accurate lesion segmentation based on endoscopy images is a fundamental task for the
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …
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 …
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains
Ultra-high field 7T MRI scanners, while producing images with exceptional anatomical
details, are cost prohibitive and hence highly inaccessible. In this paper, we introduce a …
details, are cost prohibitive and hence highly inaccessible. In this paper, we introduce a …