Digital Repository

Image Analysis and Feature extraction based on Colorectal Cancer Histology

Show simple item record

dc.contributor.author Perera, K. L. S. K. T
dc.date.accessioned 2022-03-15T03:43:54Z
dc.date.available 2022-03-15T03:43:54Z
dc.date.issued 2021
dc.identifier.citation Perera, K. L. S. K. T (2021) Image Analysis and Feature extraction based on Colorectal Cancer Histology. BSc. Dissertation Informatics Institute of Technology en_US
dc.identifier.issn 2017317
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/963
dc.description.abstract " Image-based artificial intelligence and deep learning has shown its expert-level of accuracy with an increasing rate of researchers in the medical field domain on solving various classification problems. As we all know, cancer is something that should be avoided before its spread. Since that, premature diagnosis could affect positively, and time is an essential component for a way of elimination vice versa. After the emergence of a patient to the doctor, if the doctor assumes that the symptoms are associated with a cancer, to test this, the patient requires to go through a biopsy test which is one of the mandatory ways of verification on the related issue. This could be the usual way of analyzing a cancer. However, with the research investigations it showed that in Sri Lanka it will take 12 to 14 days to get the results of the given biopsy. What this test does is that a sample of tissue taken from the body of the patient that the doctor might need to inspect will be examined more closely. These tissues will be analyzed with a microscopic anatomy where histology comes into play. Using the histology, the spread of tissue variations will be analyzed. Depending on the results, the patient might have to go under special treatments as soon as possible. In this study, the author mainly focused on developing a Convolutional neural network on analyzing and identifying tissue variations of different given histology resolutions. This included a training model of classification on identified 8 tissue types that could present on a given histology, a classification mechanism of classifying microscopic anatomy which is a digital pathology. With all the considerations mentioned above, it was proven that the requirement of such a system is essential in gaining predictions for a country like Sri Lanka. For a disease like cancer, even one day is important for a patient who diagnoses a carcinoma, and the treatments should take place then and there. " en_US
dc.language.iso en en_US
dc.subject Convolutional neural networks en_US
dc.subject Neural networks en_US
dc.subject Deep learning en_US
dc.subject Machine learning en_US
dc.subject Computational and Artificial Intelligence en_US
dc.title Image Analysis and Feature extraction based on Colorectal Cancer Histology en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Advanced Search

Browse

My Account