AIMC Topic: Radionuclide Imaging
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An end-to-end multi-task system of automatic lesion detection and anatomical localization in whole-body bone scintigraphy by deep learning.
Bioinformatics (Oxford, England)
Jan 1, 2023
SUMMARY: Limited by spatial resolution and visual contrast, bone scintigraphy interpretation is susceptible to subjective factors, which considerably affects the accuracy and repeatability of lesion detection and anatomical localization. In this work...
The deep radiomic analytics pipeline.
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Dec 1, 2022
Radiomics refers to the process of extracting useful imaging features from radiological data. Conventional radiomics like standard uptake value, intensity histograms, or phase images involve hand-crafted (manual) or automated regions of interest (com...
Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?
Medicine
Nov 25, 2022
BACKGROUND: The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in...
Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.
Optics express
Jul 4, 2022
We present a parallel Monte Carlo (MC) simulation platform for rapidly generating synthetic common-path optical coherence tomography (CP-OCT) A-scan image dataset for image-guided needle insertion. The computation time of the method has been evaluate...
Influence of Robot-Assisted Partial Nephrectomy on Long-Term Renal Function as Assessed Using 99m-Tc DTPA Renal Scintigraphy.
Journal of endourology
May 1, 2022
The long-term split renal function after robot-assisted partial nephrectomy (RAPN) is yet to be elucidated. This study aimed to assess long-term renal function of RAPN, using renal scintigraphy, and to identify clinical factors related to deteriorat...
[[SPECT] 5. Application of Artificial Intelligence in Nuclear Medicine for SPECT].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2022
Artificial Intelligence and Nuclear Medicine. Today is already the future.
Revista espanola de medicina nuclear e imagen molecular
Jan 1, 2022
Deep learning for intelligent diagnosis in thyroid scintigraphy.
The Journal of international medical research
Jan 1, 2021
OBJECTIVE: To construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy.
Study of the Usefulness of Bone Scan Index Calculated From 99m-Technetium- Hydroxymethylene Diphosphonate (Tc-HMDP) Bone Scintigraphy for Bone Metastases from Prostate Cancer Using Deep Learning Algorithms.
Current medical imaging
Jan 1, 2021
BACKGROUND: BSI calculated from bone scintigraphy using technetium-methylene diphosphonate (Tc-MDP) is used as a quantitative indicator of metastatic bone involvement in bone metastasis diagnosis, therapeutic effect assessment, and prognosis predicti...
Multiple Slice k-space Deep Learning for Magnetic Resonance Imaging Reconstruction.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Magnetic resonance imaging (MRI) has been one of the most powerful and valuable imaging methods for medical diagnosis and staging of disease. Due to the long scan time of MRI acquisition, k-space under-samplings is required during the acquisition pro...
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