Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging
Abstract Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature selection and region classification depen...
Saved in:
| Main Authors: | K. Murugan, SatheeshKumar Palanisamy, N. Sathishkumar, Tagrid Abdullah N. Alshalali |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-09638-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An automated pheochromocytoma and paraganglioma lesion segmentation AI-model at whole-body 68Ga- DOTATATE PET/CT
by: Fahmida Haque, et al.
Published: (2024-11-01) -
Automatic cervical tumors segmentation in PET/MRI by parallel encoder U-net
by: Shuai Liu, et al.
Published: (2025-06-01) -
Cross-correlation-based signal pruning method (CCSPM) for effective signal distortion reduction in massive MIMO communications
by: M. Kasiselvanathan, et al.
Published: (2025-07-01) -
A Multi-Scale Interpretability-Based PET-CT Tumor Segmentation Method
by: Dangui Yang, et al.
Published: (2025-03-01) -
3D printing of radioactive wall-less PET phantoms improves threshold-based target delineation and quantification
by: Adrian Jun Zounek, et al.
Published: (2025-06-01)