PT Journal
AU Francesco Ciompi
   Oriol Pujol
   Carlo Gatta
   Marina Alberti
   Simone Balocco
   Xavier Carrillo
   J. Mauri
   Petia Radeva
TI HoliMab: A Holistic Approach for Media-Adventitia Border Detection in Intravascular Ultrasound
SO Medical Image Analysis
JI MIA
PY 2012
BP 1085
EP 1100
VL 16
IS 6
DI 10.1016/j.media.2012.06.008
DE Media–Adventitia border detection; Intravascular ultrasound; Multi-Scale Stacked Sequential Learning; Error-correcting output codes; Holistic segmentation
AB We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed.
ER