scholarly journals Medical Image Processing: Detection and Prediction of PCOS – A Systematic Literature Review

2021 ◽  
pp. 80-98
Author(s):  
Siji Jose Pulluparambil ◽  
Subrahmanya Bhat
Keyword(s):  
Image Processing ◽  
Literature Review ◽  
Medical Image ◽  
Polycystic Ovary ◽  
Detection System ◽  
Medical Image Processing ◽  
Data Sets ◽  
Ultrasound Images ◽  
Effective Diagnosis ◽  
Reproductive Aged Women

Purpose: Considered as the most common hormonal disorder among women, polycystic ovary syndrome or PCOS affects 1 in 10 reproductive aged women (18 - 44 years). Ultrasonography is applied for assessing the ovaries to detect PCOS. The patients affected by PCOS consist of 10-12 cysts present in the ovary, but more than 10 cysts are more enough to diagnose the disorder from the ultrasound images. Then, by examining the ultrasound the presence of follicles will be determined. Therefore, the image processing approaches have assisted to identify the characteristics like follicle size, number of follicles and structure to minimize the workload and time of doctors. PCOS do not have better treatment and effective diagnosis. This paper includes reviewing a summary of some of the researches that have been going in area of medical diagnosis. Based on the review, research gap, research agendas to carry out further research are identified. Approach: A detailed study on the algorithms used in medical image processing and classification. Findings: The study indicated that most of the classification of polycystic ovarian syndrome is done merely on the clinical data sets. The new hybrid methodology proposed will be more precise as both images and lifestyle are analysed. Originality: The type of data required for detection system are studied and the architecture and schematic diagram of a proposed system are included. Paper Type: Literature Review.

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.

scholarly journals Medical Image Processing and COVID-19: A Literature Review and Bibliometric Analysis

2021 ◽  
Author(s):  
Rabab Ali ◽  
Mehrbakhsh Nilashi ◽  
Muhammed Yousoof Ismail ◽  
Ashwaq Alhargan ◽  
Abdullah Alghamdi ◽  
...  
Keyword(s):  
Image Processing ◽  
Literature Review ◽  
Bibliometric Analysis ◽  
Medical Image ◽  
Medical Image Processing

scholarly journals 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.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

scholarly journals The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Author(s):  
Kostas Marias
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Biomarker Discovery ◽  
Medical Image Processing ◽  
Machine Learning Techniques ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Precision Oncology

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

Recent advances in medical image processing for the evaluation of chronic kidney disease

2021 ◽  
Vol 69 ◽  
pp. 101960
Author(s):  
Israa Alnazer ◽  
Pascal Bourdon ◽  
Thierry Urruty ◽  
Omar Falou ◽  
Mohamad Khalil ◽  
...  
Keyword(s):  
Image Processing ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Medical Image ◽  
Medical Image Processing ◽  
Recent Advances

Research on nano-CT medical image processing based on embedded system

2021 ◽  
Vol 82 ◽  
pp. 103755
Author(s):  
Shengyan Cai ◽  
Fangyuan Chai ◽  
Chunhuan Hu ◽  
Xue Han ◽  
Shuyu Liu
Keyword(s):  
Image Processing ◽  
Embedded System ◽  
Medical Image ◽  
Medical Image Processing
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