Recent improvements in CT software allow rapid and high-quality two-dimensional reformatting of scans of the spine. Reformatting involves computer interpolation of two-dimensional multislice images acquired during routine axial CT scanning in order to generate a three-dimensional volume of data. From this block of data, new images are created and displayed in any desired plane. Reformatted images are acquired within minutes following axial CT scanning.
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Computed tomography plays an ever-increasing role in the management of fractures and dislocations due to its capability in efficiently providing multiplanar reformats and 3-dimensional volume rendered images. It can reveal findings that are occult on plain radiography and therefore allow for more accurate decision making with regard to fracture classification and management. Clinical radiologists play a critical role in facilitating the processing of imaging to provide adequate image reformats in the desired planes, producing 3 dimensional images but most crucially identifying pertinent findings, which will contribute between the selection of nonoperative and operative management and potentially influence surgical technique.
View Article and Find Full Text PDFPlanning transcatheter pulmonary valve implantation in the dysfunctional native RVOT: A semi-automated pipeline for dynamic analysis based on 4D-CT imaging.
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Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
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Division of Sleep Medicine, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California. Electronic address:
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Evaluation of the clinical utility of lateral cephalometry reconstructed from computed tomography extracted by artificial intelligence.
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Department of Oral and Maxillofacial Surgery, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Republic of Korea. Electronic address:
This study assessed the accuracy and reliability of artificial intelligence (AI)-reconstructed images of two-dimensional (2D) lateral cephalometric analyses of facial computed tomography (CT) images, which is widely used for the diagnosis of craniofacial deformities and in the planning of their treatment. Facial CT datasets from 40 patients were collected. Original 1 mm slices were reformatted to 3 mm, and then an AI algorithm reconstructed the 3 mm slices and converted them back to 1 mm to generate lateral cephalometric images.
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