Deep learning techniques for medical image segmentation: achievements and challenges

MH Hesamian, W Jia, X He, P Kennedy - Journal of digital imaging, 2019 - Springer
Deep learning-based image segmentation is by now firmly established as a robust tool in
image segmentation. It has been widely used to separate homogeneous areas as the first …

Vision 20/20: perspectives on automated image segmentation for radiotherapy

G Sharp, KD Fritscher, V Pekar, M Peroni… - Medical …, 2014 - Wiley Online Library
Due to rapid advances in radiation therapy (RT), especially image guidance and treatment
adaptation, a fast and accurate segmentation of medical images is a very important part of …

V-net: Fully convolutional neural networks for volumetric medical image segmentation

F Milletari, N Navab, SA Ahmadi - 2016 fourth international …, 2016 - ieeexplore.ieee.org
Convolutional Neural Networks (CNNs) have been recently employed to solve problems
from both the computer vision and medical image analysis fields. Despite their popularity …

Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks

K Men, J Dai, Y Li - Medical physics, 2017 - Wiley Online Library
Purpose Delineation of the clinical target volume (CTV) and organs at risk (OAR s) is very
important for radiotherapy but is time‐consuming and prone to inter‐observer variation …

Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network

X Dong, Y Lei, S Tian, T Wang, P Patel… - Radiotherapy and …, 2019 - Elsevier
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 …

[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 …

Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer

M La Macchia, F Fellin, M Amichetti, M Cianchetti… - Radiation …, 2012 - Springer
Purpose To validate, in the context of adaptive radiotherapy, three commercial software
solutions for atlas-based segmentation. Methods and materials Fifteen patients, five for each …

Automatic delineation of the clinical target volume and organs at risk by deep learning for rectal cancer postoperative radiotherapy

Y Song, J Hu, Q Wu, F Xu, S Nie, Y Zhao, S Bai… - Radiotherapy and …, 2020 - Elsevier
Background and purpose Manual delineation of clinical target volumes (CTVs) and organs
at risk (OARs) is time-consuming, and automatic contouring tools lack clinical validation. We …

[HTML][HTML] Implementing cone-beam computed tomography-guided online adaptive radiotherapy in cervical cancer

CE Shelley, MA Bolt, R Hollingdale… - Clinical and …, 2023 - Elsevier
Background and purpose Adaptive radiotherapy (ART) in locally advanced cervical cancer
(LACC) has shown promising outcomes. This study investigated the feasibility of cone-beam …

Deformable image registration for contour propagation from CT to cone-beam CT scans in radiotherapy of prostate cancer

M Thor, JBB Petersen, L Bentzen, M Høyer… - Acta …, 2011 - Taylor & Francis
Background and purpose. Daily organ motion occurring during the course of radiotherapy in
the pelvic region leads to uncertainties in the doses delivered to the tumour and the organs …