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Found 7 papers, 1 papers with code
The Optimal Input-Independent Baseline for Binary Classification: The Dutch Draw
The goal of this paper is to examine all baseline methods that are independent of feature values and determine which model is the `best' and why.
Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions
In this work, we compare five deep learning solutions to automatically segment the resection cavity in postoperative MRI.
The Dutch Draw: Constructing a Universal Baseline for Binary Prediction Models
Summarizing, the DD baseline is: (1) general, as it is applicable to all binary classification problems; (2) simple, as it is quickly determined without training or parameter-tuning; (3) informative, as insightful conclusions can be drawn from the results.
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance.
Jasmine: A New Active Learning Approach to Combat Cybercrime
These approaches choose speci? fic unlabeled instances by a query function that are expected to improve overall classi? cation performance.
Registration of ultrasound volumes based on Euclidean distance transform
Therefore, our aim with this work is to improve the registration of intraoperative US volumes.
Image and Video Processing
A Ray-based Approach for Boundary Estimation of Fiber Bundles Derived from Diffusion Tensor Imaging
Using DTI data, fiber bundles can be determined, to gain information about eloquent brain structures.
