A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
Deep transfer learning based classification model for COVID-19 disease
The COVID-19 infection is increasing at a rapid rate, with the availability of limited number of
testing kits. Therefore, the development of COVID-19 testing kits is still an open area of …
testing kits. Therefore, the development of COVID-19 testing kits is still an open area of …
[HTML][HTML] Deep learning techniques to diagnose lung cancer
L Wang - Cancers, 2022 - mdpi.com
Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …
research directions of deep learning techniques for lung cancer and pulmonary nodule …
[HTML][HTML] A novel hand-crafted with deep learning features based fusion model for COVID-19 diagnosis and classification using chest X-ray images
COVID-19 pandemic is increasing in an exponential rate, with restricted accessibility of rapid
test kits. So, the design and implementation of COVID-19 testing kits remain an open …
test kits. So, the design and implementation of COVID-19 testing kits remain an open …
FSS-2019-nCov: A deep learning architecture for semi-supervised few-shot segmentation of COVID-19 infection
The newly discovered coronavirus (COVID-19) pneumonia is providing major challenges to
research in terms of diagnosis and disease quantification. Deep-learning (DL) techniques …
research in terms of diagnosis and disease quantification. Deep-learning (DL) techniques …
Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET
I Domingues, G Pereira, P Martins, H Duarte… - Artificial Intelligence …, 2020 - Springer
Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
Relational modeling for robust and efficient pulmonary lobe segmentation in CT scans
Pulmonary lobe segmentation in computed tomography scans is essential for regional
assessment of pulmonary diseases. Recent works based on convolution neural networks …
assessment of pulmonary diseases. Recent works based on convolution neural networks …
A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
[HTML][HTML] Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …
to medical imaging, their applications increased significantly to become a trend. Likewise …