A two-view ultrasound CAD system for spina bifida detection using Zernike features
Küçük Resim Yok
Tarih
2011
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Spie-Int Soc Optical Engineering
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this work, we address a very specific CAD (Computer Aided Detection/Diagnosis) problem and try to detect one of the relatively common birth defects - spina bifida, in the prenatal period. To do this, fetal ultrasound images are used as the input imaging modality, which is the most convenient so far. Our approach is to decide using two particular types of views of the fetal neural tube. Transcerebellar head (i.e. brain) and transverse (axial) spine images are processed to extract features which are then used to classify healthy (normal), suspicious (probably defective) and non-decidable cases. Decisions raised by two independent classifiers may be individually treated, or if desired and data related to both modalities are available, those decisions can be combined to keep matters more secure. Even more security can be attained by using more than two modalities and base the final decision on all those potential classifiers. Our current system relies on feature extraction from images for cases (for particular patients). The first step is image preprocessing and segmentation to get rid of useless image pixels and represent the input in a more compact domain, which is hopefully more representative for good classification performance. Next, a particular type of feature extraction, which uses Zernike moments computed on either B/W or gray-scale image segments, is performed. The aim here is to obtain values for indicative markers that signal the presence of spina bifida. Markers differ depending on the image modality being used. Either shape or texture information captured by moments may propose useful features. Finally, SVM is used to train classifiers to be used as decision makers. Our experimental results show that a promising CAD system can be actualized for the specific purpose. On the other hand, the performance of such a system would highly depend on the qualities of image preprocessing, segmentation, feature extraction and comprehensiveness of image data.
Açıklama
Conference on Medical Imaging 2011 - Computer-Aided Diagnosis -- FEB 15-17, 2011 -- Lake Buena Vista, FL
Anahtar Kelimeler
Spina Bifida, Computer Aided Detection/Diagnosis, Segmentation, Zernike Moments, SVM, Computer-Aided Diagnosis, Masses
Kaynak
Medical Imaging 2011: Computer-Aided Diagnosis
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
7963
