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Found 18 papers, 5 papers with code
Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases
Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally.
RegWSI: Whole Slide Image Registration using Combined Deep Feature- and Intensity-Based Methods: Winner of the ACROBAT 2023 Challenge
The proposed method does not require any fine-tuning to a particular dataset and can be used directly for any desired tissue type and stain.
DeeperHistReg: Robust Whole Slide Images Registration Framework
DeeperHistReg is a software framework dedicated to registering whole slide images (WSIs) acquired using multiple stains.
Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders
However, even the synthetic ground-truth generation is time-consuming and limits the data heterogeneity, thus the deep models' generalizability.
Deep Learning-Based Segmentation of Tumors in PET/CT Volumes: Benchmark of Different Architectures and Training Strategies
The results for the HECKTOR dataset ranged from 0. 75 to 0. 76 for the aggregated Dice coefficient.
TopCoW: Benchmarking Topology-Aware Anatomical Segmentation of the Circle of Willis (CoW) for CTA and MRA
The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology.
Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge
We propose a fully automated algorithm based on deep encoder-decoder architecture.
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
For the medical domain, we present a large collection of anatomical shapes (e. g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems.
Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects
We show that it is possible to generate dozens of thousands of defective skulls with compatible defects that achieve a trade-off between defect heterogeneity and the realistic shape of the skull.
High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers
The problem of the automatic cranial defect reconstruction can be formulated as the shape completion task and solved using dedicated deep networks.
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications.
Why is the winner the best?
The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning.
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
Unsupervised Method for Intra-patient Registration of Brain Magnetic Resonance Images based on Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge
The importance of this task motivated researchers to organize the BraTS-Reg challenge, jointly with IEEE ISBI 2022 and MICCAI 2022 conferences.
Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling
The goal of this work is to propose a robust, fast, and fully automatic method for personalized cranial defect reconstruction and implant modeling.
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.
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed.
Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm
In this paper, we present a short description of the method proposed to ANHIR challenge organized jointly with the IEEE ISBI 2019 conference.
