Language: | Slovenian |
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Year of publishing: | 2024 |
Typology: | 2.11 - Undergraduate Thesis |
Organization: | UL FRI - Faculty of Computer and Information Science |
Publisher: | [M. Bažec] |
UDC: | 004.85:618.19-006(043.2) |
COBISS: |
212440323
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Views: | 92 |
Downloads: | 207 |
Average score: | 0 (0 votes) |
Metadata: |
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Secondary language: | English |
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Secondary title: | Prediction of cancer on mammographic images |
Secondary abstract: | Breast cancer is a major medical concern for people everywhere. The advent of deep learning introduces options to assist medical personnel in combating the disease. In this work we used deep learning methods to predict the presence of breast cancer on patients with tumorous lesions. We develop a pipeline that includes a segmentation and classification model. The first determines the location of the lesion and the second determines weather the lesion is benign or malign. Our goal was to reach the performance of contemporary models in the field and test our approach on a custom dataset of mammographic images. Despite initial success with our classification model, the evaluation of the final pipeline did not achieve the desired results. The reason for this is the segmentation model, which failed to detect several potential lesions in the input image. |
Secondary keywords: | breast cancer;segmentation;classification;deep learning;convolutional neural networks;computer and information science;diploma;Rak dojke;Globoko učenje (strojno učenje);Računalništvo;Univerzitetna in visokošolska dela; |
Type (COBISS): | Bachelor thesis/paper |
Study programme: | 1000468 |
Embargo end date (OpenAIRE): | 1970-01-01 |
Thesis comment: | Univ. v Ljubljani, Fak. za računalništvo in informatiko |
Pages: | 1 spletni vir (1 datoteka PDF (36 str.)) |
ID: | 25392602 |