Interactive lung segmentation in abnormal human and animal chest CT scans

Abstract: Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors' aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans.

multislice; segmentation; diseases; computerised tomography; image classification; image segmentation; lung; medical disorders; medical image processing; statistical analysis; user interfaces; lung segmentation; interactive; thoracic ct; computer‐aided diagnosis; cad; computerised tomographs; haemocytometers; learning machines; digital computing; data processing equipment or methods; image data processing or generation; inference methods or devices; lungs; tissues; computed tomography; medical image segmentation; image scanners; radiologists; computer software; medical image reconstruction; comparative animal models; animal experiment; animal model; article; classification algorithm; computer assisted tomography; cone beam computed tomography; controlled study; experimental pig; human; interactive lung segmentation; lung parenchyma; micro-computed tomography; mouse; nonhuman; normal human; radiological procedures; radiologist; algorithm; animal; artificial intelligence; automated pattern recognition; chronic disease; computer assisted tomography; disease model; lung transplantation; pig; pneumonia; procedures; radiography; thorax radiography; three dimensional imaging; time; tuberculosis; algorithms; animals; disease models; humans; mice; pattern recognition; automated; thoracic; swine; time; tomography; x-ray comput

Interactive lung segmentation in abnormal human and animal chest CT scans Articles