Deep learning techniques, which use a massive technology known as convolutional neural
networks, have shown excellent results in a variety of areas, including image processing …

The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung
cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule …

The method outlined in this paper employs transfer learning and adversarial training to
enhance the precision of pneumonia identification in chest X-rays. The authors use the …

Lung cancer is one of the leading causes of cancer-related deaths worldwide. To reduce the
mortality rate, early detection and proper treatment should be ensured. Computer-aided …

With the advent of the Deep learning era, an unprecedented change has come in the field of
medical image analysis via CAD (Computer-Aided Diagnosis)[1]–[13] system. With feature …

Background: Cancer is a deadly disease. It is crucial to diagnose cancer in its early stages.
This can be done with medical imaging. Medical imaging helps us scan and view internal …

Lung CAD system can provide auxiliary third-party opinions for doctors, improve the
accuracy of lung nodule recognition. The selection and fusion of nodule features and the …

Diabetic Retinopathy is a retinal abnormality which is characterized by progressive damage
to the retina, eventually leading to irreversible blindness. In this paper, we propose an …

Traditional methods for ancient mural segmentation have drawbacks, including fuzzy target
boundaries and low efficiency. Targeting these problems, this study proposes a pyramid …

Cervical cancer predominately affects women compared to lung, breast and endometrial
cancer. Premature stage identification and proper treatment of this cancer may lead to 100 …