Title :
Ultrasonic tissue characterization-assessment of prostate tissue malignancy in vivo using a conventional classifier based tissue classification approach and elastographic imaging
Author :
Lorenz, A. ; Pesavento, A. ; Scheipers, U. ; Ermer, H. ; Garcia-Schurmann, M. ; Sommerfeld, H.-J. ; Senge, T. ; Philippou, S.
Author_Institution :
Lorenz & Pesavento IT, Bochum, Germany
Abstract :
We present the development of a combined system which is able to exploit the benefits of two methods used for tissue characterization, strain imaging and tissue classification using a trainable classification system. Our system is able to acquire in vivo multi-compression rf-data for the calculation of the tissue strain, i.e. the elastic properties of tissue, induced by tissue compression. At the same time a neuro-fuzzy classification system is used to map the tissue malignancy. In vivo classification results and in vivo strain images are presented. The images of the two new modalities are compared to demonstrate the advantages and restrictions of both methods
Keywords :
biomechanics; biomedical ultrasonics; cancer; fuzzy neural nets; image classification; image segmentation; image sequences; inference mechanisms; medical image processing; motion estimation; pattern clustering; strain measurement; tumours; carcinoma; classifier based tissue classification; combined system; elastographic imaging; fuzzy inference; image segmentation; in vivo assessment; in vivo multicompression RF-data; lateral motion estimation; mountain clustering; neuro-fuzzy classification; optical flow cross-correlation; prostate tissue malignancy; strain imaging; tissue compression; tissue elastic properties; trainable classification system; ultrasonic tissue characterization; Capacitive sensors; Elasticity; Image analysis; Image coding; Image segmentation; Image texture analysis; In vivo; Neoplasms; Probes; Ultrasonic imaging;
Conference_Titel :
Ultrasonics Symposium, 2000 IEEE
Conference_Location :
San Juan
Print_ISBN :
0-7803-6365-5
DOI :
10.1109/ULTSYM.2000.921683