Deep learning based kidney segmentation for glomerular filtration rate measurement using quantitative SPECT/CT

J Park, S Bae, S Seo, JI Bang, WW Lee, JS Lee - 2018 - Soc Nuclear Med
26 Objectives: Glomerular filtration rate (GFR), the rate at which the kidney filters the waste
from the blood, is considered the most useful test to measure the level of renal function and …

[HTML][HTML] Measurement of glomerular filtration rate using quantitative SPECT/CT and deep-learning-based kidney segmentation

J Park, S Bae, S Seo, S Park, JI Bang, JH Han… - Scientific reports, 2019 - nature.com
Quantitative SPECT/CT is potentially useful for more accurate and reliable measurement of
glomerular filtration rate (GFR) than conventional planar scintigraphy. However, manual …

Deep learning-based SPECT/CT quantification of 177Lu uptake in the kidneys

T Ryden, M van Essen, J Svensson, P Bernhardt - 2020 - Soc Nuclear Med
1401 Introduction: The aim of this study was to develop an automated algorithm to quantify
activity concentration in the kidneys in Lu-177 SPECT images. The manual routine to …

ACTIVITY CONCENTRATION ESTIMATION IN AUTOMATED KIDNEY SEGMENTATION BASED ON CONVOLUTION NEURAL NETWORK METHOD FOR 177LU …

J Khan, T Rydèn, M Van Essen… - Radiation Protection …, 2021 - academic.oup.com
For 177Lu-DOTATATE treatments, dosimetry based on manual kidney segmentation from
computed tomography (CT) is accurate but time consuming and might be affected by …

[HTML][HTML] Healthy kidney segmentation in the dce-Mr images using a convolutional neural network and temporal signal characteristics

A Klepaczko, E Eikefjord, A Lundervold - Sensors, 2021 - mdpi.com
Quantification of renal perfusion based on dynamic contrast-enhanced magnetic resonance
imaging (DCE-MRI) requires determination of signal intensity time courses in the region of …

Clinical utility of a 3D convolutional neural network kidney segmentation method for radionuclide dosimetry

N Lamba, H Wan, A Kruzer, E Platt, A Nelson - 2019 - Soc Nuclear Med
267 Objectives: With the recent approvals of new molecular radiotherapy agents, new
methods for measurement and assessment of absorbed dose in both normal regions and …

[HTML][HTML] Deep learning renal segmentation for fully automated radiation dose estimation in unsealed source therapy

P Jackson, N Hardcastle, N Dawe, T Kron… - Frontiers in …, 2018 - frontiersin.org
Background Convolutional neural networks (CNNs) have been shown to be powerful tools
to assist with object detection and—like a human observer—may be trained based on a …

Deep regression using 99mTc-DTPA dynamic renal imaging for automatic calculation of the glomerular filtration rate

Y Pi, Z Zhao, P Yang, J Cheng, L Jiang, J Wei… - European …, 2023 - Springer
Objectives To develop and evaluate an artificial intelligence (AI) system that can
automatically calculate the glomerular filtration rate (GFR) from dynamic renal imaging …

[HTML][HTML] Automated and robust organ segmentation for 3D-based internal dose calculation

M Nazari, LD Jiménez-Franco, M Schroeder, A Kluge… - EJNMMI research, 2021 - Springer
Purpose In this work, we address image segmentation in the scope of dosimetry using deep
learning and make three main contributions:(a) to extend and optimize the architecture of an …

[HTML][HTML] PSMA-PET improves deep learning-based automated CT kidney segmentation

J Leube, M Horn, PE Hartrampf, AK Buck… - … für Medizinische Physik, 2023 - Elsevier
For dosimetry of radiopharmaceutical therapies, it is essential to determine the volume of
relevant structures exposed to therapeutic radiation. For many radiopharmaceuticals, the …