(C) Cohort-level (n= 50) BCR status prediction AUCs are shown based on 6 pathologists’ diagnoses of 3 image slices (individual and consensus), the diagnosis from standard post-operative histopathology of the whole prostatect...
We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, ...
as: F1 = 2 Precision Precision × + Recall Recall (1) where Precision is the proportion of true positives among the voxels that are classified as positive and Recall is the proportion of voxels that are classified as positives among the voxels that are positive in the ground-truth dataset. ...
Pandi SS, Chiranjeevi VR, Kalpana B, Preethi J (2023) A novel approach for pathology detection using CNN based image registration techniques. In: 2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), IEEE, ...
Unsupervised discovery of tissue architecture in multiplexed imaging Article 31 October 2022 Harnessing non-destructive 3D pathology Article 15 February 2021 Tutorial: methods for three-dimensional visualization of archival tissue material Article 29 October 2021 Data...
It is worth noting that even a small number of training images (as used in the current study) can build up models capable of accurate segmentation for the entire CBCT dataset. In the current study, despite the different dentition intraorally and the different number of tooth buds in the ...
Mrbrains 2018 FLAIR, T1w, T1gd,T2w 8 240x240x48 9 or 4 0.5 IXI brain development Dataset T1,T2 no labels 581 (110~150)x256x256 - 8.7 MICCAI Gleason 2019 Challenge 2D pathology images ~250 5K x 5K - 2.5Preliminary resultsVisual results on Iseg-2017Iseg...
The Convolutional neural network (CNN) has made significant strides in the medical domain. CNN excels at the extraction of highly representative features in acute medical pathology. Amidst the network layers, CNN allows classification Through the process of filtering, selecting, and implementing these ...
b Volume rendered image of the 3D CMRA dataset is shown. Abbreviations: CMRA, coronary magnetic resonance angiography; CCTA, coronary computed tomography angiography; LAD, left anterior descending artery; RCA, right coronary artery; SVC, superior vena cava; AO, aorta; PA, pulmonary artery Full ...
INSIHGT bridges the gap between 3D histology and traditional 2D pathology in current clinical practice The bio-orthogonal nature of the INSIHGT chemical system underlies its non-destructiveness. To highlight the clinical impact of INSIHGT in addition to 3D imaging of human samples, we found that...