NDLI: Extraction of muscle areas from ultrasonographic images using refined histogram stretching and fascia information

Content Provider	IEEE Xplore Digital Library
Author	Kwang-Baek Kim Sungshin Kim Suhyun Park Young Woon Woo
Copyright Year	2008
Description	Author affiliation: Dept. of Multimedia Eng., Dong-Eui Univ., Busan (Young Woon Woo) \|\| Sch. of Electr. Eng., Pusan Nat. Univ., Busan (Sungshin Kim) \|\| Div. of Comput. & Inf. Eng., Silla Univ., Busan (Kwang-Baek Kim) \|\| Div. of Comput. Inf. Eng., Dongseo Univ., Busan (Suhyun Park)
Abstract	Ultrasonography constructs pictures of areas inside the body needs in diagnosis by bouncing ultrasound off internal tissues or organs. In constructing an ultrasonographic image, the weakness of bounding signals induces noises and detailed differences of brightness, so that having a difficulty in detecting and diagnosing with the naked eyes in the analysis of ultrasonogram. Especially, the difficulty is extended when diagnosing muscle areas by using ultrasonographic images in the musculoskeletal test. In this paper, we propose a novel image processing method that computationally extracts a muscle area from an ultrasonographic image to assist in diagnosis. An ultrasonographic image consists of areas corresponding to various tissues and internal organs. The proposed method, based on features of intensity distribution, morphology and size of each area, extracts areas of the fascia, the subcutaneous fat and other internal organs, and then extracts a muscle area enclosed by areas of the fascia. In the extraction of areas of the fascia, a series of image processing methods such as histogram stretching, multiple operation, binarization and area connection by labeling is applied. A muscle area is extracted by using features on relative position and morphology of areas for the fascia and muscle areas. The performance evaluation using real ultrasonographic images and specialistspsila analysis show that the proposed method is able to extract target areas being approximate to real muscle areas.
Starting Page	69
Ending Page	74
File Size	3440731
Page Count	6
File Format	PDF
ISBN	9781424427246
DOI	10.1109/BICTA.2008.4656706
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-28
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ultrasonic imaging Noise Muscles Feature extraction Fascia Data mining Pixel
Content Type	Text
Resource Type	Article

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