1 code implementation • 29 Oct 2024 • Ming Kang, Fung Fung Ting, Raphaël C. -W. Phan, Chee-Ming Ting
In this paper, we propose a new You Only Look Once (YOLO)-based detection model that incorporates Pretrained Knowledge (PK), called PK-YOLO, to improve the performance for brain tumor detection in multiplane MRI slices.
1 code implementation • 22 Apr 2024 • Ming Kang, Fung Fung Ting, Raphaël C. -W. Phan, ZongYuan Ge, Chee-Ming Ting
Our ablation study demonstrates the importance of the proposed modules with CNN-Transformer networks and the convolutional blocks in Transformer for improving the performance of brain tumor segmentation with missing modalities.
no code implementations • 30 Jan 2024 • Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël Phan
Medical image semantic segmentation techniques can help identify tumors automatically from computed tomography (CT) scans.
1 code implementation • 11 Dec 2023 • Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël C. -W. Phan
We propose a novel Attentional Scale Sequence Fusion based You Only Look Once (YOLO) framework (ASF-YOLO) which combines spatial and scale features for accurate and fast cell instance segmentation.
1 code implementation • 22 Sep 2023 • Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël C. -W. Phan
You Only Look Once (YOLO)-based object detectors have shown remarkable accuracy for automated brain tumor detection.
1 code implementation • 31 Jul 2023 • Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël C. -W. Phan
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection.
1 code implementation • 26 Jun 2023 • Ming Kang, Chee-Ming Ting, Fung Fung Ting, Raphaël Phan
Blood cell detection is a typical small-scale object detection problem in computer vision.