Forensic Imaging

Forensic Imaging - ISSN 2666-2264
Source Normalized Impact per Paper (SNIP): 0.553 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 0.384 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Volumes: Volumes 20-23
Issues: 4 issues
ISSN: 26662264

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Description

Official Publication of the International Society of Radiology and Imaging (ISFRI).

Formerly known as Journal of Forensic Radiology and Imaging (JOFRI), Forensic Imaging is the first and only journal dedicated to all aspects of forensic imaging and its implications for forensic medicine.

Forensic Imaging covers various noninvasive and minimally invasive examination methods in a forensic context, mainly around the context of postmortem imaging, but also in conjunction with clinical forensic cases. Research subjects that are associated with these domains also include forensic veterinary investigations, forensic anthropology, as well as the use of 3D data acquired with a variety of imaging sensors.

Forensic Imaging seeks to publish cutting-edge research, best practices, and new approaches by presenting evidence-based reviews, original research, technical notes, brief communications, and case-studies of scientific relevance across the following areas:

  • Radiological examinations: x-ray, computed tomography (CT), magnetic resonance imaging (MRI), angiography, ultrasound, micro-CT, micro-MRI
  • Surface examinations: photogrammetry, 3D scanner technology, forensic photogrammetry
  • Computer-assisted reality: virtual reality, augmented reality, crime scene reconstruction
  • Data processing: rendering techniques, visualization tools, segmentation, 3D printing, image fusion
  • Specific nonimaging examinations: magnetic resonance spectroscopy, Hounsfield unit profiling, material differentiation
  • Artificial intelligence: machine learning, deep learning