Over the past few decades, the enormous expansion of medical data has led to searching
for ways of data analysis in smart healthcare systems. Acquisition of data from pictures …

Nuclear-derived morphological features and biomarkers provide relevant insights regarding
the tumour microenvironment, while also allowing diagnosis and prognosis in specific …

Subtype classification is critical in the treatment of gliomas because different subtypes lead
to different treatment options and postoperative care. Although many radiological-or …

Accurate T-staging is important when planning personalized radiotherapy. However, T-
staging via manual slice-by-slice inspection is time-consuming while tumor sizes and …

We provide in this paper a comprehensive comparison of various transfer learning strategies
and deep learning architectures for computer-aided classification of adult-type diffuse …

Pulmonary disease is a commonly occurring abnormality throughout this world. The
pulmonary diseases include Tuberculosis, Pneumothorax, Cardiomegaly, Pulmonary …

With the advent of digitization into radiology prior to pathology, many individualized
Computer Aided Diagnosis (CAD) systems have been modelled separately using Deep …

In this paper, we address the problem of brain tumor classification from radiology and
histopathology data. A coarse-to-fine classification approach is adopted using a combination …

Gliomas are recognized as the prevailing type of primary brain tumors. The automated
segmentation of these tumors from 3D magnetic resonance imaging (MRI) plays a key role …

Medical imaging is a cornerstone of therapy and diagnosis in modern medicine. However,
the choice of imaging modality for a particular theranostic task typically involves trade-offs …