Towards a guideline for evaluation metrics in medical image segmentation
In the last decade, research on artificial intelligence has seen rapid growth with deep
learning models, especially in the field of medical image segmentation. Various studies …
learning models, especially in the field of medical image segmentation. Various studies …
Data augmentation for medical imaging: A systematic literature review
Abstract Recent advances in Deep Learning have largely benefited from larger and more
diverse training sets. However, collecting large datasets for medical imaging is still a …
diverse training sets. However, collecting large datasets for medical imaging is still a …
Medical image data augmentation: techniques, comparisons and interpretations
E Goceri - Artificial Intelligence Review, 2023 - Springer
Designing deep learning based methods with medical images has always been an attractive
area of research to assist clinicians in rapid examination and accurate diagnosis. Those …
area of research to assist clinicians in rapid examination and accurate diagnosis. Those …
COVID-19 image classification using deep learning: Advances, challenges and opportunities
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …
[HTML][HTML] Medical image processing and COVID-19: a literature review and bibliometric analysis
RA Abumalloh, M Nilashi, MY Ismail, A Alhargan… - Journal of infection and …, 2022 - Elsevier
COVID-19 crisis has placed medical systems over the world under unprecedented and
growing pressure. Medical imaging processing can help in the diagnosis, treatment, and …
growing pressure. Medical imaging processing can help in the diagnosis, treatment, and …
[Retracted] Automatic COVID‐19 Lung Infection Segmentation through Modified Unet Model
S Shamim, MJ Awan, A Mohd Zain… - Journal of healthcare …, 2022 - Wiley Online Library
The coronavirus (COVID‐19) pandemic has had a terrible impact on human lives globally,
with far‐reaching consequences for the health and well‐being of many people around the …
with far‐reaching consequences for the health and well‐being of many people around the …
AI-based automatic segmentation of craniomaxillofacial anatomy from CBCT scans for automatic detection of pharyngeal airway evaluations in OSA patients
This study aims to generate and also validate an automatic detection algorithm for
pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a …
pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a …
A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022
KC Santosh, D GhoshRoy, S Nakarmi - Healthcare, 2023 - mdpi.com
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes
One of the primary challenges in applying deep learning approaches to medical imaging is
the limited availability of data due to various factors. These factors include concerns about …
the limited availability of data due to various factors. These factors include concerns about …
[HTML][HTML] Automated Lung Segmentation from Computed Tomography Images of Normal and COVID-19 Pneumonia Patients
F Gholamiankhah, S Mostafapour… - Iranian Journal of …, 2022 - ncbi.nlm.nih.gov
Background: Automated image segmentation is an essential step in quantitative image
analysis. This study assesses the performance of a deep learning-based model for lung …
analysis. This study assesses the performance of a deep learning-based model for lung …