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92 results on '"Ngah, Umi Kalthum"'

1. Segmentation of Breast Regions in Mammogram Based on Density: A Review

Author

Saidin, Nafiza, Sakim, Harsa Amylia Mat, Ngah, Umi Kalthum, and Shuaib, Ibrahim Lutfi

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and is described as breast density. Most of the studies are focused on the classification methods for glandular tissue detection. Others highlighted on the segmentation methods for fibroglandular tissue, while few researchers performed segmentation of the breast anatomical regions based on density. There have also been works on the segmentation of other specific parts of breast regions such as either detection of nipple position, skin-air interface or pectoral muscles. The problems on the evaluation performance of the segmentation results in relation to ground truth are also discussed in this paper., Comment: 9 pages, 2 figures,IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 2, July 2012

Published
2012

4. A Hybrid PSO-FSVM Model and Its Application to Imbalanced Classification of Mammograms

Author

Samma, Hussein, Lim, Chee Peng, Ngah, Umi Kalthum, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Selamat, Ali, editor, Nguyen, Ngoc Thanh, editor, and Haron, Habibollah, editor

Published
2013
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6. The Determination of the Number of Suspicious Clustered Micro Calcifications on ROI of Mammogram Images

Author

Siong, Ting Shyue, Mat Isa, Nor Ashidi, Nordin, Zailani Mohd., Ngah, Umi Kalthum, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Badioze Zaman, Halimah, editor, Robinson, Peter, editor, Petrou, Maria, editor, Olivier, Patrick, editor, Schröder, Heiko, editor, and Shih, Timothy K., editor

Published
2009
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8. Automatic Detection of Breast Tumours from Ultrasound Images Using the Modified Seed Based Region Growing Technique

Author

Isa, Nor Ashidi Mat, Sabarudin, Shahrill, Ngah, Umi Kalthum, Zamli, Kamal Zuhairi, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Khosla, Rajiv, editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2005
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9. Mammographic Image and Breast Ultrasound Based Expert System for Breast Diseases

Author

Ngah, Umi Kalthum, Ping, Chan Choy, Aziz, Shalihatun Azlin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Negoita, Mircea Gh., editor, Howlett, Robert J., editor, and Jain, Lakhmi C., editor

Published
2004
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16. A BI-RADS based expert systems for the diagnoses of breast diseases

Author

Ngah, Umi Kalthum, Aziz, Shalihatun Azlin, Aziz, Mohd. Ezane, Murad, Mazeda, Nik Mahdi, Nik Munirah, Mat Shakaff, Ali Yeon, Mat Isa, Nor Ashidi, Mashor, Mohd. Yusoff, and Arshad, Mohd. Rizal

Subjects
Expert systems -- Health aspects, Expert systems -- Research, Breast diseases -- Diagnosis, Breast diseases -- Research, Diagnostic imaging -- Health aspects, Diagnostic imaging -- Research, Science and technology
Abstract

Abstract: We proposed an expert system based on the interpretation of mammographic and ultrasound images that may be used by expert and non-expert doctors in the interpretation and classifying of patient cases. The expert system software consists of a mammographic(MAMMEX) and breast ultrasound(SOUNDEX) medical expert systems which may be used to deduce cases according to the Breast Imaging Recording and Data System (BI-RADS) based upon patients' history, physical and clinical assessment as well as mammograms and breast ultrasound images. The systems were tested on a total of 179 retrospective cases from the Radiology Department, Hospital Universiti Sains Malaysia (HUSM), Kubang Kerian, Kelantan. The accuracy, sensitivity and specificity of MAMMEX were 97%, 96% and 92% and values of 99%, 98% and 100% were found for SOUNDEX respectively. Key Words: Expert Systems, Knowledge-Based Systems, Mammograph, Ultrasound, Breast Cancer, INTRODUCTION Breast cancer is the most common form of malignant disease amongst women. However, mortality rates fell noticeably especially in the United Kingdom partly because of the widespread practice of [...]

Published
2007

28. Computer Aided Detection of Breast Density and Mass, and Visualization of Other Breast Anatomical Regions on Mammograms Using Graph Cuts

Author

Saidin, Nafiza, Mat Sakim, Harsa Amylia, Ngah, Umi Kalthum, Lutfi Shuaib, Ibrahim, Saidin, Nafiza, Mat Sakim, Harsa Amylia, Ngah, Umi Kalthum, and Lutfi Shuaib, Ibrahim

Abstract

Breast cancer mostly arises from the glandular (dense) region of the breast. Consequently, breast density has been found to be a strong indicator for breast cancer risk.Therefore, there is a need to develop a systemwhich can segment or classify dense breast areas. In a dense breast, the sensitivity of mammography for the early detection of breast cancer is reduced. It is difficult to detect a mass in a breast that is dense.Therefore, a computerized method to separate the existence of a mass from the glandular tissues becomes an important task.Moreover, if the segmentation results provide more precise demarcation enabling the visualization of the breast anatomical regions, it could also assist in the detection of architectural distortion or asymmetry. This study attempts to segment the dense areas of the breast and the existence of a mass and to visualize other breast regions (skin-air interface, uncompressed fat, compressed fat, and glandular) in a system.The graph cuts (GC) segmentation technique is proposed. Multiselection of seed labels has been chosen to provide the hard constraint for segmentation of the different parts.The results are promising. A strong correlation (

Published
2013

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