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

Techniques from the field of artificial intelligence, and more specifically machine (deep)
learning methods, have been core components of most recent developments in the field of …

Landslides are catastrophic natural hazards that often lead to loss of life, property damage,
and economic disruption. Image-based landslide investigations are crucial for determining …

The analysis of multi-modality positron emission tomography and computed tomography
(PET-CT) images for computer-aided diagnosis applications (eg, detection and …

Despite the great media attention for artificial intelligence (AI), for many health care
professionals the term and the functioning of AI remain a “black box,” leading to exaggerated …

Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …

The aim of this review is to provide readers with an update on the state of the art, pitfalls,
solutions for those pitfalls, future perspectives, and challenges in the quickly evolving field of …

Gross tumor volume (GTV) and clinical target volume (CTV) delineation are two critical steps
in the cancer radiotherapy planning. GTV defines the primary treatment area of the gross …

Recently, deep learning, especially convolutional neural networks, has achieved the
remarkable results in natural image classification and segmentation. At the same time, in the …

Liver lesion segmentation is an essential process to assist doctors in hepatocellular
carcinoma diagnosis and treatment planning. Multi-modal positron emission tomography …