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Image Search Results


Trends of LEEP, NCE, and H-Score with respect to accuracy using ViTB-16 model on mammogram (Mg), ultrasound (US), and X-ray images.

Journal: Scientific Reports

Article Title: Development and evaluation of a multistage transfer learning framework for robust medical image analysis

doi: 10.1038/s41598-026-42157-z

Figure Lengend Snippet: Trends of LEEP, NCE, and H-Score with respect to accuracy using ViTB-16 model on mammogram (Mg), ultrasound (US), and X-ray images.

Article Snippet: We utilized the ViTB-16 model based MSTL approach to train and test on chest CT scan ( https://www.kaggle.com/datasets/mohamedhanyyy/chest-ctscan-images/data ) and brain tumor MRI ( https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset/data ) datasets using the same parameters and settings as in the MSTL approach used in this study to generate results in Table .

Techniques:

Grad-CAM output of the proposed MSTL approach on sample randomly chosen images using ViTB-16 model.

Journal: Scientific Reports

Article Title: Development and evaluation of a multistage transfer learning framework for robust medical image analysis

doi: 10.1038/s41598-026-42157-z

Figure Lengend Snippet: Grad-CAM output of the proposed MSTL approach on sample randomly chosen images using ViTB-16 model.

Article Snippet: We utilized the ViTB-16 model based MSTL approach to train and test on chest CT scan ( https://www.kaggle.com/datasets/mohamedhanyyy/chest-ctscan-images/data ) and brain tumor MRI ( https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset/data ) datasets using the same parameters and settings as in the MSTL approach used in this study to generate results in Table .

Techniques: