Search Results for author: Vatsal Sodha

Found 2 papers, 2 papers with code

Models Genesis

1 code implementation9 Apr 2020 Zongwei Zhou, Vatsal Sodha, Jiaxuan Pang, Michael B. Gotway, Jianming Liang

Transfer learning from natural images to medical images has been established as one of the most practical paradigms in deep learning for medical image analysis.

Anatomy Self-Supervised Learning +1

Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis

2 code implementations19 Aug 2019 Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang

More importantly, learning a model from scratch simply in 3D may not necessarily yield performance better than transfer learning from ImageNet in 2D, but our Models Genesis consistently top any 2D approaches including fine-tuning the models pre-trained from ImageNet as well as fine-tuning the 2D versions of our Models Genesis, confirming the importance of 3D anatomical information and significance of our Models Genesis for 3D medical imaging.

Anatomy Brain Tumor Segmentation +6

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