Biomedical engineering. Image processing in the fight against breast cancer

1993 ◽  
Vol 2 (1) ◽  
pp. 41
Author(s):  
John Kotre
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Biomedical Engineering

AUTOMATIC SEGMENTATION OF BREAST TISSUE THERMAL IMAGES

2018 ◽  
Vol 30 (03) ◽  
pp. 1850024 ◽  
Author(s):  
Zeinab Heidari ◽  
Mehrdad Dadgostar ◽  
Zahra Einalou
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Breast Imaging ◽  
Breast Tissue ◽  
Early Stage ◽  
Automatic Segmentation ◽  
Image Data ◽  
Thermal Images ◽  
Early Stages ◽  
Invasive Method

Breast cancer is one of the main causes of women’s death. Thermal breast imaging is one the non-invasive method for cancer at early stage diagnosis. In contrast to mammography this method is cheap and painless and it can be used during pregnancy while ionized beams are not used. Specialists are seeking new ways to diagnose the cancer in early stages. Segmentation of the breast tissue is one of the most indispensable stages in most of the cancer diagnosis methods. By the advancement of infrared precise cameras, new and fast computers and nouvelle image processing approaches, it is feasible to use thermal imaging for diagnosis of breast cancer at early stages. Since the breast form is different in individuals, image segmentation is a hard task and semi-automatic or manual methods are usual in investigations. In this research the image data base of DMR-IR has been utilized and a now automatic approach has been proposed which does not need learning. Data were included 159 gray images used by dynamic protocol (132 healthy and 27 patients). In this study, by combination of different image processing methods, the segmentation of thermal images of the breast tissues have been completed automatically and results show the proper performance of recommended method.

Detection of Blood-Related Diseases Using Deep Neural Nets

2019 ◽  
pp. 1-15
Author(s):  
Rajithkumar B. K. ◽  
Shilpa D. R. ◽  
Uma B. V.
Keyword(s):  
Image Processing ◽  
Biomedical Engineering ◽  
Medical Diagnosis ◽  
Blood Smear ◽  
Neural Nets ◽  
Laboratory Methods ◽  
Intelligent Algorithms ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Traditional Image

Image processing offers medical diagnosis and it overcomes the shortcomings faced by traditional laboratory methods with the help of intelligent algorithms. It is also useful for remote quality control and consultations. As machine learning is stepping into biomedical engineering, there is a huge demand for devices which are intelligent and accurate enough to target the diseases. The platelet count in a blood sample can be done by extrapolating the number of platelets counted in the blood smear. Deep neural nets use multiple layers of filtering and automated feature extraction and detection and can overcome the hurdle of devising complex algorithms to extract features for each type of disease. So, this chapter deals with the usage of deep neural networks for the image classification and platelets count. The method of using deep neural nets has increased the accuracy of detecting the disease and greater efficiency compared to traditional image processing techniques. The method can be further expanded to other forms of diseases which can be detected through blood samples.

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

Breast Cancer Prediction and Trail Using Machine Learning and Image Processing

2021 ◽  
pp. 957-966
Author(s):  
Y. Venugeetha ◽  
B. M. Harshitha ◽  
K. P. Charitha ◽  
K. Shwetha ◽  
V. Keerthana
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Image Processing ◽  
Cancer Prediction

scholarly journals Engineering and women's health: a slow start, but gaining momentum

2019 ◽  
Vol 9 (4) ◽  
pp. 20190017 ◽  
Author(s):  
Michele J. Grimm
Keyword(s):  
Breast Cancer ◽  
Women’S Health ◽  
Women's Health ◽  
Recent Work ◽  
Biomedical Engineering ◽  
Historical Survey ◽  
Slow Start ◽  
Interdisciplinary Nature ◽  
The 1950S ◽  
Near Future

While biomedical engineers have participated in research studies that focus on understanding aspects particular to women's health since the 1950s, the depth and breadth of the research have increased significantly in the last 15–20 years. It has been increasingly clear that engineers can lend important knowledge and analysis to address questions that are key to understanding physiology and pathophysiology related to women's health. This historical survey identifies some of the earliest contributions of engineers to exploring aspects of women's health, from the behaviour of key tissues, to issues of reproduction and breast cancer. In addition, some of the more recent work in each area is identified and areas deserving additional attention are described. The interdisciplinary nature of this area of engineering, along with the growing interest within the field of biomedical engineering, promise to bring exciting new discoveries and expand knowledge that will positively impact women's health in the near future.

scholarly journals Fully automated microvessel counting and hot spot selection by image processing of whole tumour sections in invasive breast cancer

1999 ◽  
Vol 52 (3) ◽  
pp. 184-192 ◽  
Author(s):  
J. A. Belien ◽  
S. Somi ◽  
J. S. de Jong ◽  
P. J. van Diest ◽  
J. P. Baak
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Invasive Breast Cancer ◽  
Hot Spot
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