Real-Time Object Detector for Medical Diagnostics (RTMDet): A High-Performance Deep Learning Model for Brain Tumor Diagnosis
The RTMDet represents a significant advancement in the application of deep learning technologies to medical diagnostics. By optimizing the balance between computational efficiency and diagnostic precision, the RTMDet enhances the capabilities of medical imaging, potentially improving patient outcomes through faster and more accurate brain tumor detection. This model offers a promising solution for clinical settings where rapid and precise diagnostics are critical.
Authors
- Sabina Umirzakova (ORCID: https://orcid.org/0000-0002-7694-1806)
- Taeg Keun Whangbo (ORCID: https://orcid.org/0000-0003-1409-0580)
- Akmalbek Bobomirzaevich Abdusalomov (ORCID: https://orcid.org/0000-0001-5923-8695)
- Muhammadjon Musaev (ORCID: https://orcid.org/0000-0002-9355-0954)
- Sanjar Bakhtiyorov
Institutions
- Gachon University (KR)
- Tashkent University of Information Technology (UZ)
- Tashkent State University of Economics (UZ)
Publication Details
- Journal
- Bioengineering
- Published
- 2025-03-11
- DOI
- https://doi.org/10.3390/bioengineering12030274
- Citations
- 6
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 5.05