Multiple ROI selection based focal liver lesion classification in ultrasound images-Reference-Cited by-同舟云学术

Multiple ROI selection based focal liver lesion classification in ultrasound images

Published:2013-02 Issue:2 Volume:40 Page:450-457
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Jeon Jae Hyun,Choi Jae Young,Lee Sihyoung,Ro Yong Man

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference24 articles.

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2. Balasubramanian, D., Srinivasan, P., & Gurupatham, R. (2007). Automatic classification of focal lesions in ultrasound liver images using principal component analysis and neural networks. In Proceedings of the 29th annual international conference of the IEEE EMBS (pp. 2134–2137).

3. Bommanna Raja, K., Madheswaran, M., & Thyagarajah, K. (2007a). Evaluation of tissue characteristic of kidney for diagnosis and classification using first order statistics and RTS invariants. In International conference on signal processing, communications and networking 2007 (pp.483–487).

4. Bommanna Raja, K., Madheswaran, M., & Thyagarajah, K. (2007d). Analysis of ultrasound kidney images using content descriptive multiple features for disorder identification and ann based classification. In 12th international conference on computer theory and applications (pp. 382–388).

5. Quantitative and qualitative evaluation of us kidney images for disorder classification using multi-scale differential features;Bommanna Raja;ICGST_BIME Journal,2007

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