Impact of lung segmentation on the diagnosis and explanation of COVID-19 in chest X-ray images
COVID-19 frequently provokes pneumonia, which can be diagnosed using imaging exams.
Chest X-ray (CXR) is often useful because it is cheap, fast, widespread, and uses less …
Chest X-ray (CXR) is often useful because it is cheap, fast, widespread, and uses less …
A survey on deep domain adaptation and tiny object detection challenges, techniques and datasets
M Muzammul, X Li - arxiv preprint arxiv:2107.07927, 2021 - arxiv.org
This survey paper specially analyzed computer vision-based object detection challenges
and solutions by different techniques. We mainly highlighted object detection by three …
and solutions by different techniques. We mainly highlighted object detection by three …
Generalizability assessment of COVID-19 3D CT data for deep learning-based disease detection
Background Artificial intelligence technologies in classification/detection of COVID-19
positive cases suffer from generalizability. Moreover, accessing and preparing another large …
positive cases suffer from generalizability. Moreover, accessing and preparing another large …
Explainable-ai in automated medical report generation using chest x-ray images
The use of machine learning in healthcare has the potential to revolutionize virtually every
aspect of the industry. However, the lack of transparency in AI applications may lead to the …
aspect of the industry. However, the lack of transparency in AI applications may lead to the …
Explanation is all you need in distillation: Mitigating bias and shortcut learning
Bias and spurious correlations in data can cause shortcut learning, undermining out-of-
distribution (OOD) generalization in deep neural networks. Most methods require unbiased …
distribution (OOD) generalization in deep neural networks. Most methods require unbiased …
Multi-task supervised contrastive learning for chest X-ray diagnosis: A two-stage hierarchical classification framework for COVID-19 diagnosis
GY Chen, CT Lin - Applied Soft Computing, 2024 - Elsevier
Global pandemics have posed great challenges, such as limited samples and the scarcity of
carefully curated datasets, in creating reliable models for chest X-ray (CXR) diagnosis. A …
carefully curated datasets, in creating reliable models for chest X-ray (CXR) diagnosis. A …
Faster ISNet for Background Bias Mitigation on Deep Neural Networks
Image background features can constitute background bias (spurious correlations) and
impact deep classifiers decisions, causing shortcut learning (Clever Hans effect) and …
impact deep classifiers decisions, causing shortcut learning (Clever Hans effect) and …
Lung Segmentation from Chest X-Ray Images Using Deeplabv3plus-Based CNN Model
As a result of technological advancements, a variety of medical diagnostic systems have
grown rapidly to support the healthcare sectors. Over the past years, there has been …
grown rapidly to support the healthcare sectors. Over the past years, there has been …
Factors determining generalization in deep learning models for scoring COVID-CT images
The COVID-19 pandemic has inspired unprecedented data collection and computer vision
modelling efforts worldwide, focused on the diagnosis of COVID-19 from medical images …
modelling efforts worldwide, focused on the diagnosis of COVID-19 from medical images …
[HTML][HTML] ISNet: Costless and implicit image segmentation for deep classifiers, with application in COVID-19 detection
PRAS Bassi, A Cavalli - 2022 - europepmc.org
This work proposes a novel deep neural network (DNN) architecture, Implicit Segmentation
Neural Network (ISNet), to solve the task of image segmentation followed by classification. It …
Neural Network (ISNet), to solve the task of image segmentation followed by classification. It …