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ACCOMP: Augmented cell competition algorithm for breast lesion demarcation in sonography.

Jie-Zhi Cheng¹, Yi-Hong Chou, Chiun-Sheng Huang

¹Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Number 1, Section 1, Jen-Ai Road, Taipei 100, Taiwan. jzcheng@ntu.edu.tw

Medical Physics

|February 10, 2011

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A new augmented cell competition (ACCOMP) algorithm offers a user-friendly, semiautomatic method for accurately segmenting breast lesions in ultrasound images, improving diagnostic analysis.

Area of Science:

Medical Imaging
Computational Pathology
Biomedical Engineering

Background:

Accurate demarcation of sonographical breast lesions is crucial for diagnosis.
Fully automatic segmentation remains a significant challenge in medical imaging.

Purpose of the Study:

To develop an image segmentation algorithm for high-quality delineation of breast lesions in sonography.
To provide a simple and user-friendly semiautomatic scheme for lesion boundary identification.

Main Methods:

Developed the augmented cell competition (ACCOMP) algorithm, inspired by visual perception and Gestalt principles.
Employed a two-pass watershed transformation for cell competition and cell-based contour grouping to identify prominent components and boundary candidates.
Evaluated the algorithm on 324 breast sonograms (199 benign, 125 malignant) and compared results to manual delineations by experienced doctors using four assessment metrics.

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Main Results:

ACCOMP-generated boundaries demonstrated comparability to manual delineations.
The modified Williams index for ACCOMP was 1.069 +/- 0.024, exceeding the threshold of 1, indicating comparable average distances to manual delineations.
ACCOMP outperformed two conventional pixel-based segmentation algorithms in boundary delineation accuracy.

Conclusions:

The ACCOMP algorithm effectively demarcates sonographic breast lesions, particularly those with complex echogenicity and shapes.
The generated boundaries provide a reliable basis for subsequent morphological and quantitative analyses in breast lesion assessment.