Computed Tomography 3D Segmentation Based on Gray-Level Histograms

3D imaging technologies like CT (Computed Tomography) and MRI (Magnetic Resonance Imaging) have represented a great advance for diagnosis. These studies are composed of many 2D grayscale images that represent slices of patient’s body, normally orthogonal to body main axis (from head to feet, normally axis Z in Cartesian representation). These slices (normally called axial slices) are good for many diagnosis issues, but sometimes it is interesting to consider the whole study as a 3D volume. This paper is about segmenting 3D volumes obtained from medical studies (mainly CT). We base ourselves on studying the statistical distribution of gray levels so that we can segment different tissues and treating them as separate 3D objects. Note than in a CT image, gray level is basically proportional to tissue density and this technique should be good to distinguish hard tissues like bones or teeth from soft ones like muscles or skin. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study used (or will use) ONLY openly available human data that were originally located at: www.aycan.de/lp/sample-dicom-images.html https://www.dicomlibrary.com/ https://www.kaggle.com/search?q=dicom+in%3Adatasets I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors