Novel Approach for Automatic Region of Interest and Seed Point Detection in CT Images Based on Temporal and Spatial Data

作     者：Zhe Liu Charlie Maere Yuqing Song 

作者机构：School of Computer Science and TelecommunicationJiangsu UniversityZhenjiangChina 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2019年第59卷第5期

页      面：669-686页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the National Natural Science Foundation of China(Nos.61772242,61572239,61402204) Research Fund for Advanced Talents of Jiangsu University(14JDG141) Qing Lan Project China Postdoctoral Science Foundation(No.2017M611737) Zhenjiang social development project(SH2016029) 

主　　题：Computed tomography image continuously adaptive mean-shift hounsfield particle-size distribution 

摘      要：Accurately finding the region of interest is a very vital step for segmenting organs in medical image *** propose a novel approach of automatically identifying region of interest in Computed Tomography Image(CT)images based on temporal and spatial *** method is a 3 stages approach,1)We extract organ features from the CT images by adopting the Hounsfield filter.2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’area and automatically detect a seed point.3)We use a novel approach to track the growing region changes across the CT image sequence in detecting region of interest,given a seed point as our *** used quantitative and qualitative analysis to measure the accuracy against the given ground truth and our results presented a better performance than other generic approaches for automatic region of interest detection of organs in abdominal CT *** the results presented in this research work,our proposed novel sequence approach method has been proven to be superior in terms of accuracy,automation and robustness.