Editing Radiology (section)

==Analysis of images==
[[File:Radiologist in San Diego CA 2010.jpg|thumb|right|A radiologist interprets medical images on a modern [[picture archiving and communication system]] (PACS) workstation. San Diego, California, 2010.]]

=== Plain, or general, radiography ===

The basic technique is optical density evaluation (i.e. histogram analysis). It is then described that a region has a different optical density, e.g. a cancer metastasis to bone can cause radiolucency. The development of this is the digital radiological subtraction. It consists in overlapping two radiographs of the same examined region and subtracting the optical densities [https://doi.org/10.1259/dmfr.20130235 Comparison of changes in dental and bone radiographic densities in the presence of different soft-tissue simulators using pixel intensity and digital subtraction analyses]. The resultant image only contains the time-dependent differences between the two examined radiographs. The advantage of this technique is the precise determination of the dynamics of density changes and the place of their occurrence. However, beforehand the geometrical adjustment and general alignment of optical density should be done [https://doi.org/10.1259/dmfr/22185098 Noise in subtraction images made from pairs of intraoral radiographs: a comparison between four methods of geometric alignment].
Another possibility of radiographic image analysis is to study second order features, e.g. digital texture analysis [https://doi.org/10.5114/AOMS.2013.33557 Basic research Textural entropy as a potential feature for quantitative assessment of jaw bone healing process] [http://www.dmp.umed.wroc.pl/en/article/2010/47/1/23/ Comparative Analysis of Three Bone Substitute Materials Based on Co-Occurrence Matrix] or fractal dimension [https://doi.org/10.2478/s11536-013-0197-y Using fractal dimension to evaluate alveolar bone defects treated with various bone substitute materials]. On this basis, it is possible to assess the places where bio-materials are implanted into the bone for the purpose of guided bone regeneration. They take an intact bone image sample (region of interest, ROI, reference site) and a sample of the implantation site (second ROI, test site) can be assessed numerically/objectively to what extent the implantation site imitates a healthy bone and how advanced is the process of bone regeneration [https://doi.org/10.3390/ma13173854 Fast-Versus Slow-Resorbable Calcium Phosphate Bone Substitute Materials—Texture Analysis after 12 Months of Observation] [https://doi.org/10.3390/ma13132935 New Oral Surgery Materials for Bone Reconstruction—A Comparison of Five Bone Substitute Materials for Dentoalveolar Augmentation]. It is also possible to check whether the bone healing process is influenced by some systemic factors [https://doi.org/10.3390/ma13163649 Influence of General Mineral Condition on Collagen-Guided Alveolar Crest Augmentation].

=== Teleradiology ===

{{main|Teleradiology}}

Teleradiology is the transmission of radiographic images from one location to another for interpretation by an appropriately trained professional, usually a radiologist or reporting radiographer. It is most often used to allow rapid interpretation of emergency room, ICU and other emergent examinations after hours of usual operation, at night and on weekends. In these cases, the images can be sent across time zones (e.g. to Spain, Australia, India) with the receiving Clinician working his normal daylight hours. However, at present, large private teleradiology companies in the U.S. currently provide most after-hours coverage employing night-working radiologists in the U.S. Teleradiology can also be used to obtain consultation with an expert or subspecialist about a complicated or puzzling case. In the U.S., many hospitals outsource their radiology departments to radiologists in India due to the lowered cost and availability of high speed internet access.{{citation needed|date=May 2024}}

Teleradiology requires a sending station, a high-speed internet connection, and a high-quality receiving station. At the transmission station, plain [[radiography|radiographs]] are passed through a digitizing machine before transmission, while CT, MRI, ultrasound and nuclear medicine scans can be sent directly, as they are already digital data. The computer at the receiving end will need to have a high-quality display screen that has been tested and cleared for clinical purposes. Reports are then transmitted to the requesting clinician.

The major advantage of teleradiology is the ability to use different time zones to provide real-time emergency radiology services around-the-clock. The disadvantages include higher costs, limited contact between the referrer and the reporting Clinician, and the inability to cover for procedures requiring an onsite reporting Clinician. Laws and regulations concerning the use of teleradiology vary among the states, with some requiring a license to practice medicine in the state sending the radiologic exam. In the U.S., some states require the teleradiology report to be preliminary with the official report issued by a hospital staff radiologist. Lastly, a benefit of teleradiology is that it might be automated with modern [[machine learning]] techniques.<ref>{{cite journal | vauthors = Wang S, Summers RM | title = Machine learning and radiology | journal = Medical Image Analysis | volume = 16 | issue = 5 | pages = 933–51 | date = July 2012 | pmid = 22465077 | pmc = 3372692 | doi = 10.1016/j.media.2012.02.005 }}</ref><ref>{{cite journal | vauthors = Zhang Z, Sejdić E | title = Radiological images and machine learning: Trends, perspectives, and prospects | journal = Computers in Biology and Medicine | volume = 108 | pages = 354–370 | date = February 2019 | pmid = 31054502 | doi = 10.1016/j.compbiomed.2019.02.017 | pmc=6531364| arxiv = 1903.11726 }}</ref><ref>{{cite journal | vauthors = Thrall JH, Li X, Li Q, Cruz C, Do S, Dreyer K, Brink J | title = Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success | journal = Journal of the American College of Radiology | volume = 15 | issue = 3 Pt B | pages = 504–508 | date = March 2018 | pmid = 29402533 | doi = 10.1016/j.jacr.2017.12.026 | s2cid = 3703894 }}</ref>
[[File:X-ray of hand, where bone age is automatically found by BoneXpert software.jpg|thumb|[[Projectional radiography|X-ray]] of a hand with calculation of [[bone age]] analysis]]