title: Temporal segmentation of lung region from MRI sequences using multiple active contours.
abstract: Segmentation of the lung is particularly difficult because of the large variation in image quality. A modified Hough transform in combination with a mask creation algorithm can robustly determine synchronous respiratory patterns. The synchronicity restriction is relaxed by applying a greedy active contour algorithm. The respiratory patterns define a point cloud near the lung region boundary representing a subjective contour. The gravitation vector field (GVF) active contour algorithm is used to create an initial segmentation exclusively based on the point cloud. A final active contours algorithm is executed to adjust the boundary to the images. The algorithm was tested with healthy subjects and COPD patients, and the result was checked through temporal registration of coronal and sagittal images.
authors.affiliation: Computational Geometry Laboratory, Escola Politécnica, São Paulo University, Brazil.
authors.forename: Renato Seiji
authors.initials: RS
authors.lastname: Tavares
authors.forename: José Miguel Manzanares
authors.initials: JM
authors.lastname: Chirinos
authors.forename: Leonardo Ishida
authors.initials: LI
authors.lastname: Abe
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Gotoh
authors.forename: Seiichiro
authors.initials: S
authors.lastname: Kagei
authors.forename: Tae
authors.initials: T
authors.lastname: Iwasawa
authors.forename: Marcos
authors.initials: M
authors.lastname: de Sales Guerra Tsuzuki
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012119:Respiration