Exploring the Adaptability of Attention U-Net for Post-operative Brain Tumor Segmentation in MRI Scans
- Title
- Exploring the Adaptability of Attention U-Net for Post-operative Brain Tumor Segmentation in MRI Scans
- Creator
- Sobha Xavier P.; Sathish P.K.; Raju G.
- Description
- This study explores the adaptability of a segmentation model, originally trained on pre-operative MRI data, in post-operative recurrent brain tumor segmentation. We utilized the Attention U-Net model for this study. In pre-operative training, the model achieved a Dice Coefficient of 0.92 and an IOU of 0.86 for brain tumor MRI segmentation. Due to the surgical artifacts in post-operative data, performance reduced with Dice Coefficient of 0.54 and an IOU of 0. To improve the performance, the model's architecture is fine-tuned by introducing dilated convolutions and residual connections. This refinement yielded improvements in results, with a Dice Coefficient of 0.68 and an IOU of 0.62 in the post-operative context. This improvement underscores the need for further research to select and adapt efficient models, retrain specific layers with an extensive collection of post-operative images, and fine-tune model parameters to enhance feature extraction during the encoding phase. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Smart Innovation, Systems and Technologies, Vol-395 SIST, pp. 333-340.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Attention U-Net; Post-operative MRI; Recurrent tumor; Residual connections
- Coverage
- Sobha Xavier P., Department of Computer Science and Engineering School of Engineering and Technology, CHRIST University, Bengaluru, India; Sathish P.K., Department of Computer Science and Engineering School of Engineering and Technology, CHRIST University, Bengaluru, India; Raju G., Department of Computer Science and Engineering School of Engineering and Technology, CHRIST University, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 21903018; ISBN: 978-981975080-1
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sobha Xavier P.; Sathish P.K.; Raju G., “Exploring the Adaptability of Attention U-Net for Post-operative Brain Tumor Segmentation in MRI Scans,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19099.