CAD BASED MEDICAL IMAGE PROCESSING: EMPHASIS TO BREAST CANCER DETECTION

2017 ◽  
Vol 12 (2) ◽  
pp. 15
Author(s):  
SINHA G.R. ◽  
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Medical Image ◽  
Medical Image Processing ◽  
Breast Cancer Detection

Breast Cancer Detection Using Image Processing and CNN Algorithm with K-Fold Cross-Validation

2021 ◽  
pp. 481-490
Author(s):  
Pruthvi Tilekar ◽  
Purnima Singh ◽  
Nagnath Aherwadi ◽  
Sagar Pande ◽  
Aditya Khamparia
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Cross Validation ◽  
Breast Cancer Detection ◽  
Fold Cross Validation

scholarly journals Breast histopathological image analysis using image processing techniques for diagnostic puposes: A methodological review

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
R Rashmi ◽  
Keerthana Prasad ◽  
Chethana Babu K Udupa
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Medical Image ◽  
Human Life ◽  
Medical Image Processing ◽  
Histopathological Analysis ◽  
Image Processing Techniques ◽  
Computer Aided ◽  
Histopathological Images ◽  
Processing Techniques

AbstractBreast cancer in women is the second most common cancer worldwide. Early detection of breast cancer can reduce the risk of human life. Non-invasive techniques such as mammograms and ultrasound imaging are popularly used to detect the tumour. However, histopathological analysis is necessary to determine the malignancy of the tumour as it analyses the image at the cellular level. Manual analysis of these slides is time consuming, tedious, subjective and are susceptible to human errors. Also, at times the interpretation of these images are inconsistent between laboratories. Hence, a Computer-Aided Diagnostic system that can act as a decision support system is need of the hour. Moreover, recent developments in computational power and memory capacity led to the application of computer tools and medical image processing techniques to process and analyze breast cancer histopathological images. This review paper summarizes various traditional and deep learning based methods developed to analyze breast cancer histopathological images. Initially, the characteristics of breast cancer histopathological images are discussed. A detailed discussion on the various potential regions of interest is presented which is crucial for the development of Computer-Aided Diagnostic systems. We summarize the recent trends and choices made during the selection of medical image processing techniques. Finally, a detailed discussion on the various challenges involved in the analysis of BCHI is presented along with the future scope.

Advancement in Research Techniques on Medical Imaging Processing for Breast Cancer Detection

2016 ◽  
Vol 6 (2) ◽  
pp. 717
Author(s):  
Sushma S J ◽  
S C Prasanna Kumar
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Medical Image ◽  
Early Stage ◽  
Medical Image Processing ◽  
Healthcare Sector ◽  
Diagnostic Tools ◽  
Success Factor ◽  
Research Activity ◽  
Effective Diagnosis

With the advancement of medical image processing, the area of the healthcare sector has started receiving the benefits of the modern arena of diagnostic tools to identify the diseases effectively. Cancer is one of the dreaded diseases, where success factor of treatment offered by medical sector is still an unsolved problem. Hence, the success factor of the treatment lies in early stage of the disease or timely detection of the disease. This paper discusses about the advancement being made in the medical image processing towards an effective diagnosis of the breast cancer from the mammogram image in radiology. There has been enough research activity with various sorts of advances techniques being implemented in the past decade. The prime contribution of this manuscript is to showcase the advancement of the technology along with illustration of the effectiveness of the existing literatures with respect to research gap.

Image processing, radiological, and clinical information fusion in breast cancer detection

2002 ◽  
Author(s):  
Hilary Alto ◽  
Rangaraj M. Rangayyan ◽  
Basel Solaiman ◽  
J. E. Leo Desautels ◽  
J. H. MacGregor
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Information Fusion ◽  
Clinical Information ◽  
Breast Cancer Detection

IMAGE PROCESSING AND COMPUTER AIDED DIAGNOSIS IN DIGITAL MAMMOGRAPHY: A CLINICAL PERSPECTIVE

1993 ◽  
Vol 07 (06) ◽  
pp. 1493-1503 ◽  
Author(s):  
ETTA D. PISANO ◽  
FAINA SHTERN
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Digital Mammography ◽  
Computer Aided Diagnosis ◽  
Breast Cancer Detection ◽  
Digital Systems ◽  
Computer Assisted ◽  
Computer Aided ◽  
Aided Diagnosis

Mammographic technology has improved dramatically in the last two decades. The advent of digitally acquired mammograms offers the possibility of further improvements in early breast cancer detection. Specifically, digital acquisition systems decouple the process of X-ray photon detection from image display by using a primary detector that directly quantifies transmitted photons. Digital systems also allow a wide dynamic range so that a wider range of tissue contrast can be appreciated. Digital systems have the capacity to bring revolutionary advantages to breast cancer detection and management (1) image processing for increased lesion conspicuity; (2) computer-aided diagnosis for enhanced radiologic interpretation; (3) teleradiology, or image transmission, as a means of bringing world-class expertise to community hospitals and remote areas; (4) improved image access and communication through digital image archiving and transmission; and (5) dynamic, or “real time” imaging for use during biopsy and localization procedures. In this article, the authors review the literature 011 the use of image processing and computer assisted diagnosis for digital mammography. Future research goals in the development of digital mammography are also discussed.

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