Objectives Machine learning (ML) for medical imaging is emerging for several organs and
image modalities. Our objectives were to provide clinicians with an overview of this field by …

Response evaluation criteria in solid tumours (RECIST) v1. 1 are currently the reference
standard for evaluating efficacy of therapies in patients with solid tumours who are included …

Artificial Intelligence (AI) continues to shape the practice of radiology, with imaging of
hepatocellular carcinoma (HCC) being of no exception. This article prepared by members of …

In follow-up CT examinations of cancer patients, therapy success is evaluated by estimating
the change in tumor size. This process is time-consuming and error-prone. We present a …

Purpose AI-assisted techniques for lesion registration and segmentation have the potential
to make CT-based tumor follow-up assessment faster and less reader-dependent. However …

Background Major society guidelines recommend transarterial chemoembolization (TACE)
as the standard of care for intermediate-stage hepatocellular carcinoma (HCC) patients …

Objectives Radiation segmentectomy using yttrium-90 plays an emerging role in the
management of early-stage HCC. However, the value of early post-treatment MRI for …

The latest developments in cancer immunotherapy, namely the introduction of immune
checkpoint inhibitors, have led to a fundamental change in advanced cancer treatments …

Follow-up assessment of lesions for cancer patients is an important part of radiologists' work.
Image registration is a key technology to facilitate this task, as it allows for the automatic …

Liver disease is a collective term for hepatic damage caused by heterogeneous etiologies
and poses a heavy health burden worldwide. Modern medical imaging, such as computed …