Results 91 to 100 of about 43,917 (250)

Rough-fuzzy clustering and unsupervised feature selection for wavelet based MR image segmentation. [PDF]

PLoS ONE, 2015
Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which
Pradipta Maji, Shaswati Roy
doaj   +1 more source

Prefer Nested Segmentation to Compound Segmentation [PDF]

arXiv, 2017
Introduction: Intra-organ radiation dose sensitivity is becoming increasingly relevant in clinical radiotherapy. One method for assessment involves partitioning delineated regions of interest and comparing the relative contributions or importance to clinical outcomes.
arxiv  

Exploring surface‐guided systems for intelligent breathing‐adapted four‐dimensional computed tomography: A comparison to infrared‐based reflective marker systems

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study evaluates the technical feasibility of adapting a surface monitoring system, designed for conventional four‐dimensional computed tomography (4DCT), to an intelligent, breathing‐adapted 4DCT and examines its potential to expand the currently limited range of supported surrogate systems.
Niklas Lackner, Andre Karius, Rainer Fietkau, Christoph Bert, Juliane Szkitsak   +4 more
wiley   +1 more source

Geometric and dosimetric evaluation of a commercial AI auto‐contouring tool on multiple anatomical sites in CT scans

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan, Alexandra Quinn, Patrick Horsley, Joseph Chan, Maegan Stewart, Regina Bromley, Jeremy Booth   +6 more
wiley   +1 more source

Quantification and dosimetric impact of intra‐fractional bladder changes during CBCT‐guided online adaptive radiotherapy for pelvic cancer treatments

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study quantitatively evaluates bladder changes and their dosimetric impact during the on‐couch adaptive process on a commercial CBCT‐based online adaptive radiotherapy (CT‐gART) platform. Methods Data from 183 fractions of ten patients receiving online ART for pelvic cancers were analyzed retrospectively.
Ingrid Valencia Lozano, Elizabeth Buss, Catherine S. Spina, David P. Horowitz, Lisa A. Kachnic, Michael Price, Yi‐Fang Wang, Reshma Munbodh   +7 more
wiley   +1 more source

SPA-UNet: A liver tumor segmentation network based on fused multi-scale features

Open Life Sciences, 2023
Liver tumor segmentation is a critical part in the diagnosis and treatment of liver cancer. While U-shaped convolutional neural networks (UNets) have made significant strides in medical image segmentation, challenges remain in accurately segmenting tumor
Li Weikun, Jia Maoning, Yang Chen, Lin Zhenyuan, Yu Yuekang, Zhang Wenhui   +5 more
doaj   +1 more source

Learning Panoptic Segmentation from Instance Contours [PDF]

arXiv, 2020
Panoptic Segmentation aims to provide an understanding of background (stuff) and instances of objects (things) at a pixel level. It combines the separate tasks of semantic segmentation (pixel level classification) and instance segmentation to build a single unified scene understanding task.
arxiv  

SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model [PDF]

arXiv, 2023
Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system. Users need to be informed/alerted whenever an AI system generates unreliable/incorrect predictions. With the introduction of the Segment Anything Model (SAM), a general foundation segmentation model, new research opportunities emerged in ...
arxiv  

A Morphological Classification Method of ECG ST-Segment Based on Curvature Scale Space [PDF]

Journal of Biosciences and Medicines, 2015
Aomalous changes in the ST segment, including ST level deviation and ST shape change, are the major parameters in clinical electrocardiogram (ECG) diagnosis of myocardial ischemia. Automatic detection of ST segment morphology can provide a more accurate evidence for clinical diagnosis of myocardial ischemia.
Sun Yining, Hu Fusong, Jingzhi Wang, Zuchang Ma, Li Chengtao, Jin Dan, Yongliang Zhang   +6 more
openaire   +2 more sources

Semi‐automated hippocampal avoidance whole‐brain radiotherapy planning

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Hippocampal avoidance whole‐brain radiotherapy (HA‐WBRT) is designed to spare cognitive function by reducing radiation dose to the hippocampus during the treatment of brain metastases. Current manual planning methods can be time‐consuming and may vary in quality, necessitating the development of automated approaches to streamline ...
Dong Joo Rhee, Subha Perni, Kelly J. Perrin, Kevin E. Casey, Alexandra O. Leone, Callistus M. Nguyen, Laurence E. Court, He Wang, Xin Wang, Eun Young Han   +9 more
wiley   +1 more source