Modified distance regularized level set evolution for brain ventricles segmentation  

作　　者：Thirumagal Jayaraman Sravan Reddy M Manjunatha Mahadevappa Anup Sadhu Pranab Kumar Dutta 

机构地区：[1]School of Medical Science and Technology,IIT Kharagpur,Kharagpur 721302,India [2]Department of Electronics and Communications,JNTUA-College of Engineering,Pulivendula 516390,India [3]EKO CT&MRI Scan Centre,Medical College,Calcutta 700073,India [4]Department of Electrical Engineering,IIT Kharagpur,Kharagpur 721302,India

出　　处：《Visual Computing for Industry,Biomedicine,and Art》2020年第1期329-340,共12页工医艺的可视计算（英文）

摘　　要：Neurodegenerative disorders are commonly characterized by atrophy of the brain which is caused by neuronal loss.Ventricles are one of the prominent structures in the brain;their shape changes,due to their content,the cerebrospinal fluid.Analyzing the morphological changes of ventricles,aids in the diagnosis of atrophy,for which the region of interest needs to be separated from the background.This study presents a modified distance regularized level set evolution segmentation method,incorporating regional intensity information.The proposed method is implemented for segmenting ventricles from brain images for normal and atrophy subjects of magnetic resonance imaging and computed tomography images.Results of the proposed method were compared with ground truth images and produced sensitivity in the range of 65%–90%,specificity in the range of 98%–99%,and accuracy in the range of 95%–98%.Peak signal to noise ratio and structural similarity index were also used as performance measures for determining segmentation accuracy:95%and 0.95,respectively.The parameters of level set formulation vary for different datasets.An optimization procedure was followed to fine tune parameters.The proposed method was found to be efficient and robust against noisy images.The proposed method is adaptive and multimodal.

关 键 词：VENTRICLES ATROPHY Segmentation Level set Diagnosis 

分 类 号：O17[理学—数学]