International Cancer Imaging Society Development Site


Our Journal - Cancer Imaging

Cancer Imaging is the official journal of ICIS, an open access, peer-reviewed journal published by BioMed Central. Original articles, as well as reviews and editorials written by international imaging experts with a subspecialty focus on oncology, are published regularly online;  sign up for alerts to keep up-to-date with the latest articles.

Cancer Imaging Impact factor is 3.153.

2019 Abstract Book

The journal encompasses CT, MRI, ultrasound, single photon and positron emission tomography, including multimodality imaging in all kinds of malignant tumours, plus new developments, techniques and innovations.

All articles published in Cancer Imaging are included in PubMed, the most widely used biomedical bibliographic database service, as well as Embase, EmCare, Google Scholar, MEDLINE, Science Citation Index and Scopus. The full text of all research articles is deposited in PubMed Central, the US National Library of Medicine's full-text repository of life science literature.

ICIS Members receive 20% discount on article-processing fees.

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Medical Imaging News -- ScienceDaily

An exception to the rule: An intact sense of smell without a crucial olfactory brain structure

Published: Mon, 11 Nov 2019 10:49:57 EST

A handful of left-handed women have excellent senses of smell, despite lacking olfactory bulbs.

To monitor cancer therapy, researchers tag CAR T cells with imaging markers

Published: Thu, 07 Nov 2019 17:05:12 EST

The researchers genetically engineered CAR T cells with molecular tags, which they were able to monitor in an animal model using position emission tomography (PET) imaging.

New X-ray technology could revolutionize how doctors identify abnormalities

Published: Thu, 07 Nov 2019 16:06:01 EST

Using ground-breaking technology, researchers are testing a new method of X-ray imaging that uses color to identify microfractures in bones. Microfractures were previously impossible to see using standard X-ray imaging.

Placenta imaging method may aid diagnosis of pregnancy complications

Published: Thu, 07 Nov 2019 09:26:02 EST

A new imaging technique to track maternal blood flow to the placenta has the potential to help diagnose several common complications in early pregnancy, according to a new study. Researchers used the technique, referred to as pseudo-continuous arterial spin labeling magnetic resonance imaging (pCASL MRI), to identify women with reduced placental blood flow who later developed one or more complications.

Most surfing injuries involve shoulder or knee, surgery usually not required

Published: Wed, 06 Nov 2019 08:55:23 EST

A new study characterizes MRI patterns of acute surfing-related injuries in patients seeking care at HSS. Researchers also report on the proportion of those injuries that required orthopedic surgical intervention. The study found that the most common injuries involved the knee or shoulder. Surgery was usually not necessary.

Zooming into cilia sheds light into blinding diseases

Published: Tue, 05 Nov 2019 13:30:41 EST

A new study reveals an unprecedented close-up view of cilia linked to blindness.

'Intelligent' metamaterial makes MRIs affordable and accessible

Published: Tue, 05 Nov 2019 11:35:03 EST

Researchers have developed a new, 'intelligent' metamaterial -- which costs less than ten dollars to build -- that could revolutionize magnetic resonance imaging (MRI), making the entire MRI process faster, safer, and more accessible to patients around the world.

Eye on research: A new way to detect and study retinoblastoma

Published: Mon, 04 Nov 2019 15:57:10 EST

Researchers advance the field of retinoblastoma research through the discovery and use of aqueous humor biopsy. Genetic tumor information not present in the blood can be detected in this fluid from the eye.

The fetal brain possesses adult-like networks

Published: Mon, 04 Nov 2019 13:04:41 EST

The fundamental organization of brain networks is established in utero during the second and third trimesters of fetal development, according to new research. The finding lays the groundwork for understanding how the prenatal period shapes future brain function.

Artificial intelligence learns muscle anatomy in CT images

Published: Thu, 31 Oct 2019 10:05:26 EDT

Scientists report a new deep learning tool based on Bayesian U-Net architecture that can segment individual muscles from CT images. The high accuracy of the results offers a new level of personalized biomechanical modeling for patients for better therapies and athletes for better performance.

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