Imaging techniques are used to capture anomalies of the human body. The captured images
must be understood for diagnosis, prognosis and treatment planning of the anomalies …

Radiomics is a process that allows the extraction and analysis of quantitative data from
medical images. It is an evolving field of research with many potential applications in …

Foundation models in deep learning are characterized by a single large-scale model trained
on vast amounts of data serving as the foundation for various downstream tasks. Foundation …

Image classification is a hot research topic in today's society and an important direction in
the field of image processing research. SVM is a very powerful classification model in …

Cancer accounts for a huge mortality rate due to its aggressiveness, colossal potential of
metastasis, and heterogeneity (causing resistance against chemotherapy). Lung and colon …

Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …

Effective fusion of global and local multi-scale features is crucial for medical image
classification. Medical images have many noisy, scattered features, intra-class variations …

The field of Medicine and Healthcare has attained revolutionary advancements in the last
forty years. Within this period, the actual reasons behind numerous diseases were unveiled …

Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …