Segmentation of Pectoral Muscle in Mammograms Using Granular Computing

In this paper, pectoral muscle segmentation was performed to study the presence of malignancy in the pectoral muscle region in mammograms. A combined approach involving granular computing and layering was employed to locate the pectoral muscle in mammograms. In most cases, the pectoral muscle is found to be triangular in shape and hence, the ant colony optimization algorithm is employed to accurately estimate the pectoral muscle boundary. The proposed method works with the left mediolateral oblique (MLO) view of mammograms to avoid artifacts. For the right MLO view, the method automatically mirrors the image to the left MLO view. The performance of this method was evaluated using the standard mini MIAS dataset (mammographic image analysis society). The algorithm was tested on 322 images and the overall accuracy of the system was about 97.47 %. The method is robust with respect to the view, shape, size and reduces the processing time. The approach correctly identifies images when the pectoral muscle is completely absent.

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Deep learning based pectoral muscle segmentation on Mammographic Image Analysis Society (MIAS) mammograms

Precision and Future Medicine ◽

10.23838/pfm.2020.00170 ◽

2021 ◽

Author(s):

Young Jae Kim ◽

Eun Young Yoo ◽

Kwang Gi Kim

Keyword(s):

Image Analysis ◽

Deep Learning ◽

Pectoral Muscle ◽

Mammographic Image ◽

Analysis Society ◽

Muscle Segmentation

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Automatic Detection of Pectoral Muscle Region for Computer-Aided Diagnosis Using MIAS Mammograms

BioMed Research International ◽

10.1155/2016/5967580 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6 ◽

Cited By ~ 6

Author(s):

Woong Bae Yoon ◽

Ji Eun Oh ◽

Eun Young Chae ◽

Hak Hee Kim ◽

Soo Yeul Lee ◽

...

Keyword(s):

Breast Cancer ◽

Automatic Segmentation ◽

Automatic Detection ◽

Pectoral Muscle ◽

Accurate Information ◽

Detection Accuracy ◽

Pixel Intensity ◽

Muscle Region ◽

Computer Aided ◽

Muscle Segmentation

The computer-aided detection (CAD) systems have been developed to help radiologists with the early detection of breast cancer. This system provides objective and accurate information to reduce the misdiagnosis of the disease. In mammography, the pectoral muscle region is used as an index to compare the symmetry between the left and right images in the mediolateral oblique (MLO) view. The pectoral muscle segmentation is necessary for the detection of microcalcification or mass because the pectoral muscle has a similar pixel intensity as that of lesions, which affects the results of automatic detection. In this study, the mammographic image analysis society database (MIAS, 322 cases) was used for detecting the pectoral muscle segmentation. The pectoral muscle was detected by using the morphological method and the random sample consensus (RANSAC) algorithm. We evaluated the detected pectoral muscle region and compared the manual segmentation with the automatic segmentation. The results showed 92.2% accuracy. We expect that the proposed method improves the detection accuracy of breast cancer lesions using a CAD system.

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Pectoral Muscle Segmentation for Digital Mammograms Based on Otsu Thresholding

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.121-126.4537 ◽

2011 ◽

Vol 121-126 ◽

pp. 4537-4541

Author(s):

Chen Chung Liu ◽

Shyr Shen Yu ◽

Chung Yen Tsai ◽

Ta Shan Tsui

Keyword(s):

Cancer Detection ◽

Pectoral Muscle ◽

Morphological Processing ◽

Breast Cancer Detection ◽

Computer Aided Detection ◽

Otsu Thresholding ◽

Expert Radiologist ◽

Analysis Society ◽

Mammogram Image ◽

Muscle Segmentation

The appearance of pectoral muscle in medio-lateral oblique (MLO) views of mammograms can increase the false positive in computer aided detection (CAD) of breast cancer detection. Pectoral muscle has to be identified and segmented from the breast region in a mammogram before further analysis. The main goal of this paper is to propose an accurate and efficient algorithm of pectoral muscle extraction on MLO mammograms. The proposed algorithm bases on the positional characteristic of pectoral muscle in a breast region to combine the iterative Otsu thresholding scheme and the mathematic morphological processing to find the rough border of the pectoral muscle. The multiple regression analysis is then employed on the rough border to obtain the accurate segmentation of the pectoral muscle. The presented algorithm is tested on the digital mammograms from the Mammogram Image Analysis Society (MIAS) database. The experimental results show that the pectoral muscle extracted by the presented algorithm approximately follows that extracted by an expert radiologist.

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Pectoral Muscle Segmentation in Mammograms Based on Cartoon-Texture Decomposition

Pattern Recognition and Image Analysis - Lecture Notes in Computer Science ◽

10.1007/978-3-319-19390-8_66 ◽

2015 ◽

pp. 587-594 ◽

Cited By ~ 1

Author(s):

Adrian Galdran ◽

Artzai Picón ◽

Estibaliz Garrote ◽

David Pardo

Keyword(s):

Pectoral Muscle ◽

Muscle Segmentation

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The breast necrosis caused by oral anticoagulant therapy

Srpski arhiv za celokupno lekarstvo ◽

10.2298/sarh180517127g ◽

2020 ◽

Vol 148 (5-6) ◽

pp. 372-375

Author(s):

Aleksandar Guzijan ◽

Radoslav Gajanin ◽

Bozana Babic ◽

Vesna Gajanin ◽

Bojan Jovanic

Keyword(s):

Anticoagulant Therapy ◽

Breast Tissue ◽

Oral Anticoagulant Therapy ◽

Pectoral Muscle ◽

Left Breast ◽

Limited Mobility ◽

Small Vessels ◽

The Right ◽

Two Stages ◽

First Time

Introduction. Described in 1943 for the first time, breast necrosis during anticoagulant therapy is only rarely encountered in clinical practice. The objective of the article is to describe a patient who underwent anticoagulant therapy and developed breast necrosis during it. Case outline. A 57-year-old female patient was admitted to hospital with pain in her left breast, which upon examination showed to be erythematous, swelled, and hard. She had started experiencing the symptoms a few days earlier, and denied having had a fever. Over the previous four weeks she had received anticoagulant treatment (acenocoumarol) as popliteal embolectomy prophylaxis. The breast was firm, edematous, of limited mobility, and with no pectoral muscle infiltration. The breast ultrasound showed a homogeneous mass, with no signs of fluid retention or suspicious lesions. Upon admission, the patient began receiving intravenous antibiotic treatment and underwent blood tests. The second day upon admission, the patient?s breast revealed a clearly demarcated area of necrotic skin. Surgical treatment was indicated. The surgery was performed in two stages, the first of which included a partial resection of the necrotic breast tissue, and the second simplex mastectomy. Histological analysis showed severe superficial necrosis, with underlying diffuse deep venous thrombosis and marked arteritis of medium and small vessels. Focal areas of extensive necrosis were found deep in the breast parenchyma. Conclusion. Considering that breast necrosis is extremely rare, it is usually not suspected initially. Learning about the patient?s undergoing anticoagulant therapy is of crucial importance for reaching the right diagnosis. Breast abscesses should also be ruled out. Surgery is the treatment of choice, as changes to the breast tissue are usually irreversible.

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Attachment distribution of pectoral muscle origins identified in dual-plane breast implant insertion

Archives of Plastic Surgery ◽

10.5999/aps.2019.00906 ◽

2020 ◽

Vol 47 (2) ◽

pp. 160-164

Author(s):

Su Bong Nam ◽

Kyung Ho Song ◽

Jung Yeol Seo ◽

June Seok Choi ◽

Tae Seo Park ◽

...

Keyword(s):

Breast Reconstruction ◽

Breast Implant ◽

Pectoralis Major Muscle ◽

Pectoral Muscle ◽

Augmentation Mammoplasty ◽

Dual Plane ◽

Reconstruction Surgery ◽

Additional Information ◽

Implant Placement ◽

The Right

Background Implant-based dual-plane augmentation mammoplasty requires accurate separation of the pectoralis major muscle (PMM) at its origins. The authors identified the PMM origins during breast reconstruction surgery with the goal of providing additional information on subpectoral implant insertion for reconstructive or aesthetic purposes.Methods This study was conducted on 67 patients who underwent breast reconstruction surgery at the breast center of our hospital between November 2016 and June 2018. In total, 34 left and 39 right hemithoraces were examined. The left and right hemithoraces were each divided into 15 zones to determine the percentage of PMM attachments in each zone. The distribution of PMM origins in each zone was examined to identify any statistically significant differences.Results There were no statistically significant differences in the origins of the PMM between the right and left hemithoraces. The percentage of attachments increased moving from the fourth to the sixth rib and from the lateral to the medial aspect.Conclusions The anatomical findings of this study could be used as a reference for accurate dissection of the origins of the PMM for the preparation of the subpectoral pocket for subpectoral implant placement.

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