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Found 5 papers, 5 papers with code
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guide
Medical image segmentation is an increasingly popular area of research in medical imaging processing and analysis.
Open-source tool for Airway Segmentation in Computed Tomography using 2.5D Modified EfficientDet: Contribution to the ATM22 Challenge
Airway segmentation in computed tomography images can be used to analyze pulmonary diseases, however, manual segmentation is labor intensive and relies on expert knowledge.
PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data
In natural language processing (NLP), there is a need for more resources in Portuguese, since much of the data used in the state-of-the-art research is in other languages.
Hippocampus Segmentation on Epilepsy and Alzheimer's Disease Studies with Multiple Convolutional Neural Networks
We test this methodology alongside other recent deep learning methods, in two domains: The HarP test set and an in-house epilepsy dataset, containing hippocampus resections, named HCUnicamp.
Extended 2D Consensus Hippocampus Segmentation
Segmentation done by experts is considered to be a gold-standard when evaluating automated methods, buts it is a time consuming and arduos task, requiring specialized personnel.
