Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

作     者：Debnath Bhattacharyya EaliStephen Neal Joshua N.Thirupathi Rao Yung-cheol Byun 

作者机构：Department of Computer Science and EngineeringKoneru Lakshmaiah Education FoundationVaddeswaramGuntur522302Andhra PradeshIndia Department of Computer Science&EngineeringVignan’s Institute of Information Technology(A)Visakhapatnam530049Andhra PradeshIndia Department of Computer EngineeringJeju National University102 Jejudaehak-roJeju-siJeju-do690-756Korea 

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

年 卷 期：2023年第75卷第4期

页      面：1447-1465页

核心收录：

学科分类：12[管理学] 08[工学] 1010[医学-医学技术（可授医学、理学学位）] 0831[工学-生物医学工程（可授工学、理学、医学学位）] 100207[医学-影像医学与核医学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 081104[工学-模式识别与智能系统] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 10[医学] 

基　　金：supported by the Ministry of SMEs and Startups (MSS),Korea,under the“Startup growth technology development program (R&D,S3125114)” by the Ministry of Small and Medium-sized Enterprises (SMEs)and Startups (MSS),Korea,under the“Regional Specialized Industry Development Plus Program (R&D,S3246057)”supervised by the Korea Institute for Advancement of Technology (KIAT) 

主　　题：Magnetic resonance imaging(MRI) lung cancer Luna-16 logistic distribution segmentation deep learning juxta plural pulmonary nodules 

摘      要：Lung cancer is the leading cause of mortality in the world affectingboth men and women *** a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are *** of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one *** the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most *** employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.