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Found 12 papers, 2 papers with code
3D Transformer based on deformable patch location for differential diagnosis between Alzheimer's disease and Frontotemporal dementia
In this paper, we present a novel 3D transformer-based architecture using a deformable patch location module to improve the differential diagnosis of Alzheimer's disease and Frontotemporal dementia.
Brain Structure Ages -- A new biomarker for multi-disease classification
Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure.
Sport Task: Fine Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2022
Since 2021, the task also provides a stroke detection challenge from unannotated, untrimmed videos.
Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis
In the first stage, we propose a deep grading model to extract meaningful features.
Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia
In this paper, we propose a deep learning based approach for both problems of disease detection and differential diagnosis.
Longitudinal detection of new MS lesions using Deep Learning
First, we propose to use transfer-learning from a model trained on a segmentation task using single time-points.
Interpretable differential diagnosis for Alzheimer's disease and Frontotemporal dementia
However, differential diagnosis of these two types of dementia remains difficult at the early stage of disease due to similar patterns of clinical symptoms.
Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligence
Current deep learning-based approaches in this field, however, have a number of drawbacks, including the interpretability of model decisions, a lack of generalizability information and a lower performance compared to traditional machine learning techniques.
Sports Video: Fine-Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2021
Sports video analysis is a prevalent research topic due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests up to analysis of athletes' performance.
DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation
Instead of proposing another improvement of the segmentation accuracy, we propose a novel method robust to domain shift and performing well on unseen datasets, called DeepLesionBrain (DLB).
AssemblyNet: A large ensemble of CNNs for 3D Whole Brain MRI Segmentation
Finally, we showed the interest of using semi-supervised learning to improve the performance of our method.
AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.
