Search Results for author:
Found 12 papers, 3 papers with code
Multiple Teachers-Meticulous Student: A Domain Adaptive Meta-Knowledge Distillation Model for Medical Image Classification
Besides, requiring bulk annotated data for model training, the large size of models, and the privacy-preserving of patients are other challenges of using DL in medical image classification.
A Cascade Transformer-based Model for 3D Dose Distribution Prediction in Head and Neck Cancer Radiotherapy
The dose distribution prediction subnet outperformed the winner of the OpenKBP2020 competition with 2. 77 and 1. 79 for dose and DVH scores, respectively.
Deepfake Detection of Occluded Images Using a Patch-based Approach
To test our approach, new datasets including real and fake images are created.
A Generalised Deep Meta-Learning Model for Automated Quality Control of Cardiovascular Magnetic Resonance Images
Methods: The proposed generalised deep meta-learning model can evaluate the quality by learning tasks in the prior stage and then fine-tuning the resulting model on a small labelled dataset of the desired tasks.
Smart ROI Detection for Alzheimer's disease prediction using explainable AI
After extracting the ROIs automatically, Alzheimer's disease is predicted using extracted ROI-based 3D CNN.
Stacked Cross-modal Feature Consolidation Attention Networks for Image Captioning
Thus, we propose a stacked cross-modal feature consolidation (SCFC) attention network for image captioning in which we simultaneously consolidate cross-modal features through a novel compounding function in a multi-step reasoning fashion.
Fully Automated Assessment of Cardiac Coverage in Cine Cardiovascular Magnetic Resonance Images using an Explainable Deep Visual Salient Region Detection Model
The accuracy of the baseline model in identifying the presence/absence of basal/apical slices is 96. 25\% and 94. 51\%, respectively, which increases to 96. 88\% and 95. 72\% after improving using the proposed salient region detection model.
A generalizable approach based on U-Net model for automatic Intra retinal cyst segmentation in SD-OCT images
Intra retinal fluids or Cysts are one of the important symptoms of macular pathologies that are efficiently visualized in OCT images.
Automatic Multi-Class Cardiovascular Magnetic Resonance Image Quality Assessment using Unsupervised Domain Adaptation in Spatial and Frequency Domains
Increasing the speed of training and testing can be achieved with the proposed model in the frequency domain.
Medical Imaging and Computational Image Analysis in COVID-19 Diagnosis: A Review
The contribution of this study is four-fold: 1) to use as a tutorial of the field for both clinicians and technologists, 2) to comprehensively review the characteristics of COVID-19 as presented in medical images, 3) to examine automated artificial intelligence-based approaches for COVID-19 diagnosis based on the accuracy and the method used, 4) to express the research limitations in this field and the methods used to overcome them.
A Weighted Multi-Criteria Decision Making Approach for Image Captioning
In this study, we present a method for visual retrieval based image captioning, in which we use a multi criteria decision making algorithm to effectively combine several criteria with proportional impact weights to retrieve the most relevant caption for the query image.
A Novel Scheme for Intelligent Recognition of Pornographic Images
To test the proposed method, performance of system was evaluated over 18354 download images from internet.
