A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
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 …
Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
A review on deep-learning algorithms for fetal ultrasound-image analysis
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …
fetal images. A number of survey papers in the field is today available, but most of them are …
Deep neural architectures for medical image semantic segmentation
MZ Khan, MK Gajendran, Y Lee, MA Khan - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning has an enormous impact on medical image analysis. Many computer-aided
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …
Federated split task-agnostic vision transformer for COVID-19 CXR diagnosis
Federated learning, which shares the weights of the neural network across clients, is gaining
attention in the healthcare sector as it enables training on a large corpus of decentralized …
attention in the healthcare sector as it enables training on a large corpus of decentralized …
Multi-task learning for quality assessment of fetal head ultrasound images
It is essential to measure anatomical parameters in prenatal ultrasound images for the
growth and development of the fetus, which is highly relied on obtaining a standard plane …
growth and development of the fetus, which is highly relied on obtaining a standard plane …
Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study
X Ye, D Guo, J Ge, S Yan, Y Xin, Y Song, Y Yan… - Nature …, 2022 - nature.com
Accurate organ-at-risk (OAR) segmentation is critical to reduce radiotherapy complications.
Consensus guidelines recommend delineating over 40 OARs in the head-and-neck (H&N) …
Consensus guidelines recommend delineating over 40 OARs in the head-and-neck (H&N) …
An ultrasound standard plane detection model of fetal head based on multi-task learning and hybrid knowledge graph
Prenatal ultrasound examination is a powerful tool to prevent birth defects and assess fetal
health. Obtaining ultrasound standard planes is a prerequisite for prenatal ultrasound …
health. Obtaining ultrasound standard planes is a prerequisite for prenatal ultrasound …
Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization
Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and
planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities …
planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities …