A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
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 …
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 …
Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network
Background and purpose Manual contouring is labor intensive, and subject to variations in
operator knowledge, experience and technique. This work aims to develop an automated …
operator knowledge, experience and technique. This work aims to develop an automated …
CT prostate segmentation based on synthetic MRI‐aided deep attention fully convolution network
Purpose Accurate segmentation of the prostate on computed tomography (CT) for treatment
planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging …
planning is challenging due to CT's poor soft tissue contrast. Magnetic resonance imaging …
Deep learning for segmentation in radiation therapy planning: a review
Segmentation of organs and structures, as either targets or organs‐at‐risk, has a significant
influence on the success of radiation therapy. Manual segmentation is a tedious and time …
influence on the success of radiation therapy. Manual segmentation is a tedious and time …
Fully automated organ segmentation in male pelvic CT images
A Balagopal, S Kazemifar, D Nguyen… - Physics in Medicine …, 2018 - iopscience.iop.org
Accurate segmentation of prostate and surrounding organs at risk is important for prostate
cancer radiotherapy treatment planning. We present a fully automated workflow for male …
cancer radiotherapy treatment planning. We present a fully automated workflow for male …
[HTML][HTML] Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network
Z Liu, X Liu, B Xiao, S Wang, Z Miao, Y Sun, F Zhang - Physica Medica, 2020 - Elsevier
Purpose We introduced and evaluated an end-to-end organs-at-risk (OARs) segmentation
model that can provide accurate and consistent OARs segmentation results in much less …
model that can provide accurate and consistent OARs segmentation results in much less …
[HTML][HTML] Clinical evaluation of deep learning and atlas-based auto-contouring of bladder and rectum for prostate radiation therapy
WJ Zabel, JL Conway, A Gladwish, J Skliarenko… - Practical Radiation …, 2021 - Elsevier
Purpose Auto-contouring may reduce workload, interobserver variation, and time associated
with manual contouring of organs at risk. Manual contouring remains the standard due in …
with manual contouring of organs at risk. Manual contouring remains the standard due in …
[HTML][HTML] Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network
Segmentation of normal organs is a critical and time-consuming process in radiotherapy.
Auto-segmentation of abdominal organs has been made possible by the advent of the …
Auto-segmentation of abdominal organs has been made possible by the advent of the …
Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer
Background and purpose Delineation of organs at risk (OARs), such as the bladder, rectum
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …
and sigmoid, plays an important role in the delivery of optimal absorbed dose to the target …