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01/17/2023
Using Large Text-to-Image Models with Structured Prompts for Skin Disease Identification: A Case Study
This paper investigates the potential usage of large text-to-image (LTI)...
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11/25/2022
A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection
Objectives: Early detection of liver fibrosis can help cure the disease ...
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11/25/2022
Automating Cobb Angle Measurement for Adolescent Idiopathic Scoliosis using Instance Segmentation
Scoliosis is a three-dimensional deformity of the spine, most often diag...
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11/10/2022
A novel GAN-based paradigm for weakly supervised brain tumor segmentation of MR images
Segmentation of regions of interest (ROIs) for identifying abnormalities...
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11/09/2022
Optimized Global Perturbation Attacks For Brain Tumour ROI Extraction From Binary Classification Models
Deep learning techniques have greatly benefited computer-aided diagnosti...
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10/13/2022
Tumor-location-guided CNNs for Pediatric Low-grade Glioma Molecular Biomarker Classification Using MRI
Pediatric low-grade glioma (pLGG) is the most common type of brain cance...
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10/03/2022
Introducing Vision Transformer for Alzheimer's Disease classification task with 3D input
Many high-performance classification models utilize complex CNN-based ar...
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09/20/2022
Superpixel Generation and Clustering for Weakly Supervised Brain Tumor Segmentation in MR Images
Training Machine Learning (ML) models to segment tumors and other anomal...
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08/22/2022
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning
Generalizability is the ultimate goal of Machine Learning (ML) image cla...
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07/29/2022
Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology
Traditional datasets for the radiological diagnosis tend to only provide...
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07/29/2022
Open-radiomics: A Research Protocol to Make Radiomics-based Machine Learning Pipelines Reproducible
The application of artificial intelligence (AI) techniques to medical im...
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06/28/2022
Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators
As deep learning is widely used in the radiology field, the explainabili...
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11/29/2021
Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning
Brain tumor segmentation is a critical task for tumor volumetric analyse...
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11/29/2021
Localized Perturbations For Weakly-Supervised Segmentation of Glioma Brain Tumours
Deep convolutional neural networks (CNNs) have become an essential tool ...
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03/03/2021
Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification
Generative Adversarial Networks can learn the mapping of random noise to...
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02/13/2021
Multi-class Generative Adversarial Nets for Semi-supervised Image Classification
From generating never-before-seen images to domain adaptation, applicati...
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11/16/2020
A Transfer Learning Based Active Learning Framework for Brain Tumor Classification
Brain tumor is one of the leading causes of cancer-related death globall...
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10/06/2020
RANDGAN: Randomized Generative Adversarial Network for Detection of COVID-19 in Chest X-ray
COVID-19 spread across the globe at an immense rate has left healthcare ...
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08/31/2020
Evaluating Knowledge Transfer In Neural Network for Medical Images
Deep learning and knowledge transfer techniques have permeated the field...
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07/02/2020
A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning
Multi-task learning (MTL) optimizes several learning tasks simultaneousl...
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06/08/2020
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account
Receiver operating characteristic (ROC) curve is an informative tool in ...
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06/05/2020
Inception Augmentation Generative Adversarial Network
Successful training of convolutional neural networks (CNNs) requires a s...
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06/01/2020
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-weighted MRI using Convolutional Neural Networks
Data augmentation refers to a group of techniques whose goal is to battl...
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11/04/2019
Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection
Convolutional Neural Networks (CNNs) have been used for automated detect...
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09/20/2019
A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI
The segmentation of prostate whole gland and transition zone in Diffusio...
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07/10/2019
Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images
As an analytic pipeline for quantitative imaging feature extraction and ...
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06/25/2019
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging
Cox proportional hazard model (CPH) is commonly used in clinical researc...
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05/30/2019
Prostate Cancer Detection using Deep Convolutional Neural Networks
Prostate cancer is one of the most common forms of cancer and the third ...
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05/23/2019
Improving Prognostic Value of CT Deep Radiomic Features in Pancreatic Ductal Adenocarcinoma Using Transfer Learning
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive ca...
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11/14/2018
ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks
Generative Adversarial Networks (GANs) have shown considerable promise f...
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05/10/2017
Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection
While lung cancer is the second most diagnosed form of cancer in men and...
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12/25/2015
Sparse Reconstruction of Compressive Sensing MRI using Cross-Domain Stochastically Fully Connected Conditional Random Fields
Magnetic Resonance Imaging (MRI) is a crucial medical imaging technology...
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12/15/2015
Noise-Compensated, Bias-Corrected Diffusion Weighted Endorectal Magnetic Resonance Imaging via a Stochastically Fully-Connected Joint Conditional Random Field Model
Diffusion weighted magnetic resonance imaging (DW-MR) is a powerful tool...
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11/11/2015
Discovery Radiomics via StochasticNet Sequencers for Cancer Detection
Radiomics has proven to be a powerful prognostic tool for cancer detecti...
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09/15/2015
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data
Good results on image classification and retrieval using support vector ...
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09/01/2015
Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction
Lung cancer is the leading cause for cancer related deaths. As such, the...
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09/01/2015
Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection
Prostate cancer is the most diagnosed form of cancer in Canadian men, an...
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07/05/2015
Autoencoding the Retrieval Relevance of Medical Images
Content-based image retrieval (CBIR) of medical images is a crucial task...
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04/23/2015