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      Acquisition, Visualization and Potential Applications of 3D Data in Anatomic Pathology

      review-article
      1 , * , 1 , 1
      Discoveries
      Applied Systems srl
      3D Data, 3D Pathology, Virtual Reality, Anatomic Pathology, Volumetric Data, 3D Scanning

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          Abstract

          Although human anatomy and histology are naturally three-dimensional (3D), commonly used diagnostic and educational tools are technologically restricted to providing two-dimensional representations (e.g. gross photography and glass slides). This limitation may be overcome by employing techniques to acquire and display 3D data, which refers to the digital information used to describe a 3D object mathematically. There are several established and experimental strategies to capture macroscopic and microscopic 3D data. In addition, recent hardware and software innovations have propelled the visualization of 3D models, including virtual and augmented reality. Accompanying these advances are novel clinical and non-clinical applications of 3D data in pathology. Medical education and research stand to benefit a great deal from utilizing 3D data as it can change our understanding of complex anatomical and histological structures. Although these technologies are yet to be adopted in routine surgical pathology, forensic pathology has embraced 3D scanning and model reconstruction. In this review, we intend to provide a general overview of the technologies and emerging applications involved with 3D data.

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          Most cited references43

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          Medical 3D Printing for the Radiologist.

          While use of advanced visualization in radiology is instrumental in diagnosis and communication with referring clinicians, there is an unmet need to render Digital Imaging and Communications in Medicine (DICOM) images as three-dimensional (3D) printed models capable of providing both tactile feedback and tangible depth information about anatomic and pathologic states. Three-dimensional printed models, already entrenched in the nonmedical sciences, are rapidly being embraced in medicine as well as in the lay community. Incorporating 3D printing from images generated and interpreted by radiologists presents particular challenges, including training, materials and equipment, and guidelines. The overall costs of a 3D printing laboratory must be balanced by the clinical benefits. It is expected that the number of 3D-printed models generated from DICOM images for planning interventions and fabricating implants will grow exponentially. Radiologists should at a minimum be familiar with 3D printing as it relates to their field, including types of 3D printing technologies and materials used to create 3D-printed anatomic models, published applications of models to date, and clinical benefits in radiology. Online supplemental material is available for this article.
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            Breast cancer histopathology image analysis: a review.

            This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.
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              Systematic review of randomized controlled trials on the effectiveness of virtual reality training for laparoscopic surgery.

              Surgical training has traditionally been one of apprenticeship. The aim of this review was to determine whether virtual reality (VR) training can supplement and/or replace conventional laparoscopic training in surgical trainees with limited or no laparoscopic experience. Randomized clinical trials addressing this issue were identified from The Cochrane Library trials register, Medline, Embase, Science Citation Index Expanded, grey literature and reference lists. Standardized mean difference was calculated with 95 per cent confidence intervals based on available case analysis. Twenty-three trials (mostly with a high risk of bias) involving 622 participants were included in this review. In trainees without surgical experience, VR training decreased the time taken to complete a task, increased accuracy and decreased errors compared with no training. In the same participants, VR training was more accurate than video trainer (VT) training. In participants with limited laparoscopic experience, VR training resulted in a greater reduction in operating time, error and unnecessary movements than standard laparoscopic training. In these participants, the composite performance score was better in the VR group than the VT group. VR training can supplement standard laparoscopic surgical training. It is at least as effective as video training in supplementing standard laparoscopic training.
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                Author and article information

                Journal
                Discoveries (Craiova)
                Discoveries (Craiova)
                Discoveries (Craiova)
                Discoveries
                Applied Systems srl
                2359-7232
                31 December 2016
                Oct-Dec 2016
                : 4
                : 4 , Recent Discoveries part 1
                : e68
                Affiliations
                [1]Mount Sinai Health System, Department of Diagnostic Pathology and Laboratory Medicine, New York, NY, USA
                Author notes
                Shyam Prajapati, DO, Mount Sinai West, Diagnostic Pathology & Laboratory Medicine, 1000 Tenth Ave, New York, NY 10019
                Article
                171
                10.15190/d.2016.15
                6941555
                9b04c6bc-b098-4bca-b82c-950c46340a91
                Copyright © 2016, Applied Systems

                This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 December 2016
                : 29 December 2016
                : 29 December 2016
                Categories
                Review Article

                3d data,3d pathology,virtual reality,anatomic pathology,volumetric data,3d scanning

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