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Pattern recognition based prediction of the outcome of radiotherapy in cervical cancer treatment

Yasar, Mohammed; Nunavath, Vimala
Master thesis
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URI
http://hdl.handle.net/11250/137533
Date
2011
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  • Master's theses in Information and Communication Technology [511]
Abstract
Cervical Cancer is one the most common cancers amongst women. Ev-

ery year almost 300 Norwegian women are diagnosed with cervical cancer.

It is the 5th most deadly cancer type amongst women in the world. Esti-

mates show that there are approximately 473,000 cases of cervical cancer

in 2008 and 253,500 deaths per year. As we can see from the statistics, cer-

vical cancer is a very severe and common type of cancer which costs many

human lives every year. Therefore any progression in prognostication of

this disease is very essential to treatment of its patients.

Our task in this project was to analyze contrast enhanced MR imaging

data from 78 patients. This data was recorded after a certain period of

time after the patients received radiotherapy. The data was collected

after a median time of 48 months for each patient. The outcome of the

treatment and propagation of the contrast medium in to the blood vessels

(in tumor region) was recorded.

The main focus of this project was to model spatial patterns in the

Cervix Cancer data set using hidden Markov models (HMM) in one of

the machine learning techniques can be used to predict the outcome of

radiotherapy treatment of the cervical cancer patients based on identi ed

patterns with given data samples.

To nd the unobserved (hidden) patterns, we have used hidden Markov

models on the dataset to nd hidden patterns in the data. These models

show the distribution of the outcome of the treatment, grouped by the

similarities between properties of the contrast medium in the blood vessels.

Our research shows that hidden Markov models are not feasible for this

dataset. It was not possible to retrieve any information with high enough

accuracy to be able to predict outcome of radiotherapy treatment.
Description
Masteroppgave i informasjons- og kommunikasjonsteknologi IKT590 2011 – Universitetet i Agder, Grimstad
Publisher
Universitetet i Agder / University of Agder

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