Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

V Cheplygina, M De Bruijne, JPW Pluim - Medical image analysis, 2019 - Elsevier
Abstract Machine learning (ML) algorithms have made a tremendous impact in the field of
medical imaging. While medical imaging datasets have been growing in size, a challenge …

Sample-efficient deep learning for COVID-19 diagnosis based on CT scans

X He, X Yang, S Zhang, J Zhao, Y Zhang, E Xing, P Xie - medrxiv, 2020 - medrxiv.org
Abstract Coronavirus disease 2019 (COVID-19) has infected more than 1.3 million
individuals all over the world and caused more than 106,000 deaths. One major hurdle in …

Automating the ABCD rule for melanoma detection: a survey

ARH Ali, J Li, G Yang - IEEE Access, 2020 - ieeexplore.ieee.org
The ABCD rule is a simple framework that physicians, novice dermatologists and non-
physicians can use to learn about the features of melanoma in its early curable stage …

Challenges and recent solutions for image segmentation in the era of deep learning

E Goceri - 2019 ninth international conference on image …, 2019 - ieeexplore.ieee.org
Image segmentation has a key role in computer vision and image processing. Superiority of
deep learning based segmentation techniques has been shown in various studies in the …

Transfer learning model for false positive reduction in lymph node detection via sparse coding and deep learning

Y Ma, Y Peng, TY Wu - Journal of Intelligent & Fuzzy Systems, 2022 - content.iospress.com
Transfer learning technique is popularly employed for a lot of medical image classification
tasks. Here based on convolutional neural network (CNN) and sparse coding process, we …

A machine learning approach to automatic detection of irregularity in skin lesion border using dermoscopic images

AR Ali, J Li, G Yang, SJ O'Shea - PeerJ Computer Science, 2020 - peerj.com
Skin lesion border irregularity is considered an important clinical feature for the early
diagnosis of melanoma, representing the B feature in the ABCD rule. In this article we …

GC-EnC: A Copula based ensemble of CNNs for malignancy identification in breast histopathology and cytology images

S Dey, S Mitra, S Chakraborty, D Mondal… - Computers in Biology …, 2023 - Elsevier
In the present work, we have explored the potential of Copula-based ensemble of CNNs
(Convolutional Neural Networks) over individual classifiers for malignancy identification in …

Effects of objects and image quality on melanoma classification using deep neural networks

BSA Gazioğlu, ME Kamaşak - Biomedical Signal Processing and Control, 2021 - Elsevier
Melanoma is a type of skin cancer with a higher mortality rates. Early and accurate diagnosis
of melanoma has critical importance on its prognosis. Recently, deep learning models …

[PDF][PDF] Deep Learning Applications for COVID-19 Analysis: A State-of-the-Art Survey.

W Li, X Deng, H Shao, X Wang - CMES-Computer Modeling in …, 2021 - cdn.techscience.cn
The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all
over the world. In this paper, the predictions of epidemiological propagation models, such as …

[PDF][PDF] Coronavirus diagnosis based on chest X-ray images and pre-trained DenseNet-121

Y Kateb, H Meglouli, A Khebli - Revue d'Intelligence Artificielle, 2023 - researchgate.net
Accepted: 5 January 2023 A serious global problem called COVID-19 has killed a great
number of people and rendered many projects useless. The obtained individual's …