AIMC Topic: Radionuclide Imaging
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Convolutional neural network-based kidney volume estimation from low-dose unenhanced computed tomography scans.
BMC medical imaging
Nov 15, 2023
PURPOSE: Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its automation are promising but mos...
Rib region detection for scanning path planning for fully automated robotic abdominal ultrasonography.
International journal of computer assisted radiology and surgery
Oct 3, 2023
PURPOSE: Scanning path planning is an essential technology for fully automated ultrasound (US) robotics. During biliary scanning, the subcostal boundary is critical body surface landmarks for scanning path planning but are often invisible, depending ...
Automated liver segmental volume ratio quantification on non-contrast T1-Vibe Dixon liver MRI using deep learning.
European journal of radiology
Aug 14, 2023
PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calculation of the liver segmental volume ratio (LSVR) on a non-contrast T1-vibe Dixon liver MRI sequence using a deep learning segmentation pipeline.
Transfer-learning is a key ingredient to fast deep learning-based 4D liver MRI reconstruction.
Scientific reports
Jul 11, 2023
Time-resolved volumetric magnetic resonance imaging (4D MRI) could be used to address organ motion in image-guided interventions like tumor ablation. Current 4D reconstruction techniques are unsuitable for most interventional settings because they ar...
Robust Detection, Segmentation, and Metrology of High Bandwidth Memory 3D Scans Using an Improved Semi-Supervised Deep Learning Approach.
Sensors (Basel, Switzerland)
Jun 9, 2023
Recent advancements in 3D deep learning have led to significant progress in improving accuracy and reducing processing time, with applications spanning various domains such as medical imaging, robotics, and autonomous vehicle navigation for identifyi...
Reducing scan time in Lu planar scintigraphy using convolutional neural network: A Monte Carlo simulation study.
Journal of applied clinical medical physics
Jun 1, 2023
PURPOSE: The aim of this study was to reduce scan time in Lu planar scintigraphy through the use of convolutional neural network (CNN) to facilitate personalized dosimetry for Lu-based peptide receptor radionuclide therapy.
The role of warm ischemia time on functional outcomes after robotic partial nephrectomy: a radionuclide renal scan study from the clock randomized trial.
World journal of urology
Apr 21, 2023
PURPOSE: To evaluate the relationship between warm ischemia time (WIT) duration and renal function after robot-assisted partial nephrectomy (RAPN).
The Past, Present, and Future Role of Artificial Intelligence in Ventilation/Perfusion Scintigraphy: A Systematic Review.
Seminars in nuclear medicine
Apr 18, 2023
Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, remain one of the few studies performed in the acute setting, and are amongst the few performed in the emergency setting. V/Q studies have witnessed a lo...
Can Deep Learning Detect Incidental Abnormal Cardiac Uptake Related to Amyloidosis on Routine Bone Scintigraphy?
JACC. Cardiovascular imaging
Apr 12, 2023
Deep Learning on Bone Scintigraphy to Detect Abnormal Cardiac Uptake at Risk of Cardiac Amyloidosis.
JACC. Cardiovascular imaging
Apr 12, 2023
BACKGROUND: Cardiac uptake on technetium-99m whole-body scintigraphy (WBS) is almost pathognomonic of transthyretin cardiac amyloidosis. The rare false positives are often related to light-chain cardiac amyloidosis. However, this scintigraphic featur...
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