Multi-tumor Detection and Analysis Based on Advance Region Quantitative Approach of Breast MRI

The proposed Advance Region Quantitative Approach (ARQA) method is used for Breast multi-tumor region segmentation which helps in decease detection and also detects the multi-tumors in different scenarios. The present approach uses the existing preprocessing methods and filters for effectual extraction and analysis of MRI images. The mass regions are well segmented and further classified as malignant disease by computing texture features based on vision gray-level co-occurrence matrices (VGCMs) and logistic regression method. The proposed algorithm is an easy approach for doctors and physicians to provide easy option for medical image analysis.

[1]  E E Sterns,et al.  Relation between clinical and mammographic diagnosis of breast problems and the cancer/biopsy rate. , 1996, Canadian journal of surgery. Journal canadien de chirurgie.

[2]  Lulu Wang,et al.  Early Diagnosis of Breast Cancer , 2017, Sensors.

[3]  Ian W. Ricketts,et al.  The Mammographic Image Analysis Society digital mammogram database , 1994 .

[4]  Anna N. Vioral,et al.  Breast Cancer Overview , 2007, Plastic surgical nursing : official journal of the American Society of Plastic and Reconstructive Surgical Nurses.

[5]  Rangaraj M. Rangayyan,et al.  Segmentation of breast tumors in mammograms by fuzzy region growing , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[6]  J.F. Head,et al.  Infrared imaging: making progress in fulfilling its medical promise , 2002, IEEE Engineering in Medicine and Biology Magazine.

[7]  C. A. Lipari,et al.  The important role of infrared imaging in breast cancer , 2000, IEEE Engineering in Medicine and Biology Magazine.

[8]  Vijay K. Jain,et al.  Markov random field for tumor detection in digital mammography , 1995, IEEE Trans. Medical Imaging.

[9]  Chronic Disease Division Cancer facts and figures , 2010 .

[10]  Rangaraj M. Rangayyan,et al.  Detection of Breast Tumor Boundaries Using ISO-Intensity Contours and Dynamic Thresholding , 1998, Digital Mammography / IWDM.

[11]  N. Cerneaz Model-based analysis of mammograms , 1994 .

[12]  Gerald Schaefer,et al.  Thermography based breast cancer analysis using statistical features and fuzzy classification , 2009, Pattern Recognit..

[13]  L. Fass Imaging and cancer: A review , 2008, Molecular oncology.

[14]  T. Button,et al.  Detection of cancerous breasts by dynamic area telethermometry , 2001, IEEE Engineering in Medicine and Biology Magazine.