Pulmonary Embolism Detection

2 papers with code • 1 benchmarks • 0 datasets

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Most implemented papers

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

MrGiovanni/ModelsGenesis 19 Aug 2019

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.

Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection

Nahid1992/CAD_PE 15 Sep 2021

At the image level, we compare convolutional neural networks (CNNs) with vision transformers, and contrast self-supervised learning (SSL) with supervised learning, followed by an evaluation of transfer learning compared with training from scratch.