title: Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.
abstract: In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.
authors.affiliation: National Institutes of Health, Bethesda, MD 20892, USA.
authors.forename: Shijun
authors.initials: S
authors.lastname: Wang
authors.forename: Matthew T
authors.initials: MT
authors.lastname: McKenna
authors.forename: Tan B
authors.initials: TB
authors.lastname: Nguyen
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Burns
authors.forename: Nicholas
authors.initials: N
authors.lastname: Petrick
authors.forename: Berkman
authors.initials: B
authors.lastname: Sahiner
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Summers
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001185:Artificial Intelligence; D023881:Colonography, Computed Tomographic / Q000379:methods*; D006801:Humans; D007417:Intestinal Polyps / Q000473:pathology; D012372:ROC Curve; D014743:Videotape Recording / Q000379:methods*