Artificial intelligence for radiation oncology applications using public datasets
Artificial intelligence (AI) has exceptional potential to positively impact the field of radiation
oncology. However, large curated datasets-often involving imaging data and corresponding …
oncology. However, large curated datasets-often involving imaging data and corresponding …
MedShapeNet--A large-scale dataset of 3D medical shapes for computer vision
Prior to the deep learning era, shape was commonly used to describe the objects.
Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly …
Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly …
Should individual timeline and serial CT/MRI panels of all patients be presented in acute brain insult cohorts? A pilot study of 45 patients with decompressive …
AH Autio, J Paavola, J Tervonen, M Lång… - Acta …, 2023 - Springer
Purpose Our review of acute brain insult articles indicated that the patients' individual (i)
timeline panels with the defined time points since the emergency call and (ii) serial brain …
timeline panels with the defined time points since the emergency call and (ii) serial brain …
Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes
Implantation of electrodes in the brain has been used as a clinical tool for decades to
stimulate and record brain activity. As this method increasingly becomes the standard of …
stimulate and record brain activity. As this method increasingly becomes the standard of …
Brain tumor segmentation (brats) challenge 2024: Meningioma radiotherapy planning automated segmentation
D LaBella, K Schumacher, M Mix, K Leu… - arXiv preprint arXiv …, 2024 - arxiv.org
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT)
challenge aims to advance automated segmentation algorithms using the largest known …
challenge aims to advance automated segmentation algorithms using the largest known …
OpenMAP‐T1: A Rapid Deep‐Learning Approach to Parcellate 280 Anatomical Regions to Cover the Whole Brain
This study introduces OpenMAP‐T1, a deep‐learning‐based method for rapid and accurate
whole‐brain parcellation in T1‐weighted brain MRI, which aims to overcome the limitations …
whole‐brain parcellation in T1‐weighted brain MRI, which aims to overcome the limitations …
Multimodal neuroimaging data from a 5-week heart rate variability biofeedback randomized clinical trial
We present data from the Heart Rate Variability and Emotion Regulation (HRV-ER)
randomized clinical trial testing effects of HRV biofeedback. Younger (N= 121) and older (N …
randomized clinical trial testing effects of HRV biofeedback. Younger (N= 121) and older (N …
[HTML][HTML] Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality
MC Vinding, R Oostenveld - NeuroImage, 2022 - Elsevier
The increasing requirements for adoption of FAIR data management and sharing original
research data from neuroimaging studies can be at odds with protecting the anonymity of the …
research data from neuroimaging studies can be at odds with protecting the anonymity of the …
FAST-AID Brain: Fast and accurate segmentation tool using artificial intelligence developed for brain
Medical images used in clinical practice are heterogeneous and not the same quality as
scans studied in academic research. Preprocessing breaks down in extreme cases when …
scans studied in academic research. Preprocessing breaks down in extreme cases when …
Automated, fast, robust brain extraction on contrast-enhanced T1-weighted MRI in presence of brain tumors: an optimized model based on multi-center datasets
Y Teng, C Chen, X Shu, F Zhao, L Zhang, J Xu - European Radiology, 2024 - Springer
Objectives Existing brain extraction models should be further optimized to provide more
information for oncological analysis. We aimed to develop an nnU-Net–based deep learning …
information for oncological analysis. We aimed to develop an nnU-Net–based deep learning …