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Conference proceeding
Multiscale Voxel Based Decoding For Enhanced Natural Image Reconstruction From Brain Activity
International Joint Conference on Neural Networks (IJCNN)
01 Jan 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Reconstructing perceived images from human brain activity monitored by functional magnetic resonance imaging (fMRI) is hard, especially for natural images. Existing methods often result in blurry and unintelligible reconstructions with low fidelity. In this study, we present a novel approach for enhanced image reconstruction, in which existing methods for object decoding and image reconstruction are merged together. This is achieved by conditioning the reconstructed image to its decoded image category using a class-conditional generative adversarial network and neural style transfer. The results indicate that our approach improves the semantic similarity of the reconstructed images and can be used as a general framework for enhanced image reconstruction.
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Details
- Title
- Multiscale Voxel Based Decoding For Enhanced Natural Image Reconstruction From Brain Activity
- Creators
- Mali Halac - Drexel UniversityMurat Isik - Drexel UniversityHasan Ayaz - Drexel UniversityAnup Das - Drexel University
- Publication Details
- International Joint Conference on Neural Networks (IJCNN)
- Conference
- 2022 International Joint Conference on Neural Networks (IJCNN) (Padua, Italy, 18 Jul 2022–23 Jul 2022)
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000867070904064
- Scopus ID
- 2-s2.0-85140764611
- Other Identifier
- 991019182653404721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Hardware & Architecture
- Engineering, Electrical & Electronic
- Neurosciences