Literature DB >> 22256194

Boundary delineation for hepatic hemangioma in ultrasound images.

Naeim Bahrami1, Seyed Hamid Rezatofighi, Aliyeh Mahdavi Adeli, S Kamaledin Setarehdan.   

Abstract

Hemangioma is one of the most common benign congenital complications of the human body which can arise in interior organs and external limbs. The main aim of this work is to present a new method for automatic detection of liver hemangioma and its boundaries in ultrasound images, using image processing techniques. Overall there are two phases, the preprocessing procedure and the boundary delineation phase. The preprocessing phase includes three main stages: 1. Image contrast enhancement using Difference of Offset Gaussian (DoOG) method, 2. Applying Canny edge filtering, 3. Applying an adaptive threshold in order to detect the ROI (hemangioma). Following, the snake algorithm is used to segment the hemangioma region in the second phase. For the quantitative assessment of the proposed method for the segmentation stage, the results derived via the proposed algorithms have been compared with the corresponding segmented regions determined by an expert using three similarity criteria. The results showed 73 percent similarity without pre-processing and 90 percent similarity with pre-processing.

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Mesh:

Year:  2011        PMID: 22256194     DOI: 10.1109/IEMBS.2011.6091970

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Kinetic and perfusion modeling of hyperpolarized (13)C pyruvate and urea in cancer with arbitrary RF flip angles.

Authors:  Naeim Bahrami; Christine Leon Swisher; Cornelius Von Morze; Daniel B Vigneron; Peder E Z Larson
Journal:  Quant Imaging Med Surg       Date:  2014-02

2.  Algorithm guided outlining of 105 pancreatic cancer liver metastases in Ultrasound.

Authors:  Alexander Hann; Lucas Bettac; Mark M Haenle; Tilmann Graeter; Andreas W Berger; Jens Dreyhaupt; Dieter Schmalstieg; Wolfram G Zoller; Jan Egger
Journal:  Sci Rep       Date:  2017-10-06       Impact factor: 4.379

  2 in total

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