Breast cancer detection using deep learning: Datasets, methods, and challenges ahead
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
Deep reinforcement learning in medical imaging: A literature review
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …
learns a sequence of actions that maximizes the expected reward, with the representative …
AWSnet: An auto-weighted supervision attention network for myocardial scar and edema segmentation in multi-sequence cardiac magnetic resonance images
Multi-sequence cardiac magnetic resonance (CMR) provides essential pathology
information (scar and edema) to diagnose myocardial infarction. However, automatic …
information (scar and edema) to diagnose myocardial infarction. However, automatic …
Stochastic‐offset‐enhanced restricted slice excitation and 180° refocusing designs with spatially non‐linear ΔB0 shim array fields
Purpose Developing a general framework with a novel stochastic offset strategy for the
design of optimized RF pulses and time‐varying spatially non‐linear ΔB0 shim array fields …
design of optimized RF pulses and time‐varying spatially non‐linear ΔB0 shim array fields …
AFFIRM: affinity fusion-based framework for iteratively random motion correction of multi-slice fetal brain MRI
Multi-slice magnetic resonance images of the fetal brain are usually contaminated by severe
and arbitrary fetal and maternal motion. Hence, stable and robust motion correction is …
and arbitrary fetal and maternal motion. Hence, stable and robust motion correction is …
[HTML][HTML] Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification
Morphological abnormalities of the femoroacetabular (hip) joint are among the most
common human musculoskeletal disorders and often develop asymptomatically at early …
common human musculoskeletal disorders and often develop asymptomatically at early …
CoDISP: Exploring Compressed Domain Camera ISP with RGB-guided Encoder
Abstract Most mobile device Image Signal Processing (ISP) pipelines operate directly on
RAW image data for all processing tasks. However the rise of super-high-resolution cameras …
RAW image data for all processing tasks. However the rise of super-high-resolution cameras …
Learn fine-grained adaptive loss for multiple anatomical landmark detection in medical images
Automatic and accurate detection of anatomical landmarks is an essential operation in
medical image analysis with a multitude of applications. Recent deep learning methods …
medical image analysis with a multitude of applications. Recent deep learning methods …
Fetal neuroimaging updates
Fetal ultrasonography (US) and MR imaging provide essential information in the evaluation
and management of pregnancies and have been shown to improve perinatal outcomes in …
and management of pregnancies and have been shown to improve perinatal outcomes in …
Automatic 3-D spine curve measurement in freehand ultrasound via structure-aware reinforcement learning spinous process localization
QY Ran, J Miao, SP Zhou, S Hua, SY He, P Zhou… - Ultrasonics, 2023 - Elsevier
Freehand 3-D ultrasound systems have been advanced in scoliosis assessment to avoid
radiation hazards, especially for teenagers. This novel 3-D imaging method also makes it …
radiation hazards, especially for teenagers. This novel 3-D imaging method also makes it …