Advanced Deep Learning for Medical Image Analysis
The application of deep learning is evolving, including in expert systems for healthcare, such as disease classification. Several challenges in the use of deep-learning algorithms in application to disease classification. The study aims to improve classification to address the problem. The thesis p...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2022
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| Online Access: | http://hdl.handle.net/20.500.11937/87912 |
| _version_ | 1848764949794390016 |
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| author | Nugroho, Bayu Adhi |
| author_facet | Nugroho, Bayu Adhi |
| author_sort | Nugroho, Bayu Adhi |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The application of deep learning is evolving, including in expert systems
for healthcare, such as disease classification. Several challenges in the use of deep-learning algorithms in application to disease classification. The study aims to improve classification to address the problem. The thesis proposes a cost-sensitive imbalance training algorithm to address an unequal number of training examples, a two-stage Bayesian optimisation training algorithm and a dual-branch network to train a one-class classification scheme, further improving classification performance. |
| first_indexed | 2025-11-14T11:27:29Z |
| format | Thesis |
| id | curtin-20.500.11937-87912 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:27:29Z |
| publishDate | 2022 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-879122022-02-24T04:18:26Z Advanced Deep Learning for Medical Image Analysis Nugroho, Bayu Adhi The application of deep learning is evolving, including in expert systems for healthcare, such as disease classification. Several challenges in the use of deep-learning algorithms in application to disease classification. The study aims to improve classification to address the problem. The thesis proposes a cost-sensitive imbalance training algorithm to address an unequal number of training examples, a two-stage Bayesian optimisation training algorithm and a dual-branch network to train a one-class classification scheme, further improving classification performance. 2022 Thesis http://hdl.handle.net/20.500.11937/87912 Curtin University fulltext |
| spellingShingle | Nugroho, Bayu Adhi Advanced Deep Learning for Medical Image Analysis |
| title | Advanced Deep Learning
for Medical Image Analysis |
| title_full | Advanced Deep Learning
for Medical Image Analysis |
| title_fullStr | Advanced Deep Learning
for Medical Image Analysis |
| title_full_unstemmed | Advanced Deep Learning
for Medical Image Analysis |
| title_short | Advanced Deep Learning
for Medical Image Analysis |
| title_sort | advanced deep learning
for medical image analysis |
| url | http://hdl.handle.net/20.500.11937/87912 |