A review of deep-learning-based medical image segmentation methods
As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …
made great contributions to sustainable medical care. Now it has become an important …
A survey on applications of deep learning in microscopy image analysis
Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
Deep-learning framework to detect lung abnormality–A study with chest X-Ray and lung CT scan images
Lung abnormalities are highly risky conditions in humans. The early diagnosis of lung
abnormalities is essential to reduce the risk by enabling quick and efficient treatment. This …
abnormalities is essential to reduce the risk by enabling quick and efficient treatment. This …
[HTML][HTML] A comprehensive comparison among metaheuristics (MHs) for geohazard modeling using machine learning: Insights from a case study of landslide …
Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …
tremendous success. However, researchers and practitioners still face challenges in …
Inception v3 based cervical cell classification combined with artificially extracted features
N Dong, L Zhao, CH Wu, JF Chang - Applied Soft Computing, 2020 - Elsevier
Traditional cell classification methods generally extract multiple features of the cell manually.
Moreover, the simple use of artificial feature extraction methods has low universality. For …
Moreover, the simple use of artificial feature extraction methods has low universality. For …
A convolutional neural network model for abnormality diagnosis in a nuclear power plant
Diagnosing abnormal events in nuclear power plants (NPPs) is a challenging issue given
the hundreds of possible abnormal events that can occur and the thousands of plant …
the hundreds of possible abnormal events that can occur and the thousands of plant …
Automated segmentation of leukocyte from hematological images—a study using various CNN schemes
Medical images play a fundamental role in disease screening, and automated evaluation of
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
these images is widely preferred in hospitals. Recently, Convolutional Neural Network …
A deep neural network and classical features based scheme for objects recognition: an application for machine inspection
Computer Vision (CV) domain is widely used in the current era of automation and visual
surveillance for the detection and classification of different objects in a diverse environment …
surveillance for the detection and classification of different objects in a diverse environment …
A self-learning deep neural network for classification of breast histopathological images
The most effective and feasible method for treating cancer is early diagnosis of breast
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …
Automatic detection of breast cancer in ultrasound images using Mayfly algorithm optimized handcrafted features
BACKGROUND: The incidence rates of breast cancer in women community is progressively
raising and the premature diagnosis is necessary to detect and cure the disease …
raising and the premature diagnosis is necessary to detect and cure the disease …