PET acquisition and reconstruction are time-consuming. A PET preview image is commonly reconstructed at the end of data acquisition of each bed-position frame in the step-and-shoot mode. We propose a scheme to reconstruct, stream, and visualize the PET preview image during acquisition to provide quasi-real-time visual feedback. As acquisition proceeds, event data are processed continuously by a backprojection method using time-of-flight kernels while corrections are applied only for sensitivity, time span, and decay. A preview update can be scheduled by frame or by a configured time interval. To create a preview image, the 3-dimensional volume of the current segment is knit with other existing segments. The knitted volume is projected onto a 2-dimensional plane, and the resultant gray-scale image is streamed to a display component for visualization. By using fast and simple reconstruction and correction, the described scheme balances processing speed and image quality to provide early and frequent visual feedback. Results show that the preview creation, streaming, and visualization time are shorter than the acquisition time for a typical whole-body study. Fast feedback is achieved during PET acquisition, which provides clinicians with an indication of data acquisition and an estimation of image quality and allows early corrective measure and image quality control if necessary.
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http://dx.doi.org/10.2967/jnmt.118.218511 | DOI Listing |
Int J Surg
December 2024
Department of Gynecological and Breast Surgery and Oncology, Pitié-Salpêtrière, Assistance Publique des Hôpitaux de Paris (AP-HP), University Hospital, Paris, France.
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View Article and Find Full Text PDFJ Microsc
December 2024
Université de Franche-Comté, CNRS, AS2M Department, FEMTO-ST Institute, Besançon, France.
This article presents a qualitative, quantitative, and experimental analysis of optical coherence tomography (OCT) volumes obtained using different families of non-raster trajectories. We propose a multicriteria analysis to be used in the assessment of scan trajectories used in obtaining OCT volumetric point cloud data. The novel criteria includes exploitation/exploration ratio of the OCT data obtained, smoothness of the scan trajectory and fast preview of the acquired OCT data in addition to conventional criteria; time and quality (expressed as volume similarity rather than slice-by-slice image quality).
View Article and Find Full Text PDFDatabase (Oxford)
December 2024
School of Computing and Mathematical Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK.
Visual analysis of peripheral blood smear slides using medical image analysis is required to diagnose red blood cell (RBC) morphological deformities caused by anemia. The absence of a complete anaemic RBC dataset has hindered the training and testing of deep convolutional neural networks (CNNs) for computer-aided analysis of RBC morphology. We introduce a benchmark RBC image dataset named Anemic RBC (AneRBC) to overcome this problem.
View Article and Find Full Text PDFJMIR Form Res
December 2024
Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany.
Background: The rapid development of large language models (LLMs) such as OpenAI's ChatGPT has significantly impacted medical research and education. These models have shown potential in fields ranging from radiological imaging interpretation to medical licensing examination assistance. Recently, LLMs have been enhanced with image recognition capabilities.
View Article and Find Full Text PDFCureus
November 2024
Hematopoiesis, Joint Research Center for Human Retrovirus Infection, Kumamoto University, Kumamoto, JPN.
Purpose The purpose of this study was to assess the ability of large language models (LLMs) to comprehend the safety management, protection methods, and proper handling of X-rays according to laws and regulations. We evaluated the performance of GPT-4o (OpenAI, San Francisco, CA, USA) and o1-preview (OpenAI) using questions from the 'Operations Chief of Radiography With X-rays' certification examination in Japan. Methods This study engaged GPT-4o and o1-preview in responding to questions from this Japanese certification examination for 'Operations Chief of Radiography With X-rays'.
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