AIMC Topic: Whole Body Imaging

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Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection.

The British journal of radiology Feb 22, 2021
OBJECTIVES: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR).
Signal-To-Noise Ratio Female Postoperative Period Humans Aged Whole Body Imaging Algorithms Contrast Media Aged, 80 and over Prospective Studies Adult Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Male Quality Control Middle Aged Radiation Dosage Neoplasms Deep Learning
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Deep learning based automated diagnosis of bone metastases with SPECT thoracic bone images.

Scientific reports Feb 19, 2021
SPECT nuclear medicine imaging is widely used for treating, diagnosing, evaluating and preventing various serious diseases. The automated classification of medical images is becoming increasingly important in developing computer-aided diagnosis syste...
Algorithms Female Reproducibility of Results Aged Humans Data Analysis Deep Learning ROC Curve Image Processing, Computer-Assisted Bone Neoplasms Aged, 80 and over Adult Male Middle Aged Image Interpretation, Computer-Assisted Automation Tomography, Emission-Computed, Single-Photon Whole Body Imaging
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Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure.

European journal of nuclear medicine and molecular imaging Feb 1, 2021
PURPOSE: To generate diagnostic F-FDG PET images of pediatric cancer patients from ultra-low-dose F-FDG PET input images, using a novel artificial intelligence (AI) algorithm.
Humans Positron-Emission Tomography Fluorodeoxyglucose F18 Radiation Exposure Whole Body Imaging Artificial Intelligence Young Adult Child Magnetic Resonance Imaging
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Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Nature communications Nov 6, 2020
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that...
Whole Body Imaging Animal Structures Deep Learning Image Processing, Computer-Assisted Mice Kidney Mice, Inbred C57BL Liver Spleen X-Ray Microtomography Reproducibility of Results Animals Male Lung Algorithms Brain Female
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Potential use of deep learning techniques for postmortem imaging.

Forensic science, medicine, and pathology Sep 29, 2020
The use of postmortem computed tomography in forensic medicine, in addition to conventional autopsy, is now a standard procedure in several countries. However, the large number of cases, the large amount of data, and the lack of postmortem radiology ...
Humans Neural Networks, Computer Postmortem Changes Whole Body Imaging Tomography, X-Ray Computed Deep Learning Forensic Medicine Autopsy
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The utility of a deep learning-based algorithm for bone scintigraphy in patient with prostate cancer.

Annals of nuclear medicine Sep 21, 2020
OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is evident in detecting bone metastasis in patients with malignant tumor including prostate cancer, as appropriate treatment and prognosis are dependent o...
Whole Body Imaging Sensitivity and Specificity Male Middle Aged Deep Learning Image Processing, Computer-Assisted Prostatic Neoplasms Bone and Bones Radionuclide Imaging Humans Aged
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Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application.

PloS one Aug 14, 2020
Bone metastasis is one of the most frequent diseases in prostate cancer; scintigraphy imaging is particularly important for the clinical diagnosis of bone metastasis. Up to date, minimal research has been conducted regarding the application of machin...
Image Interpretation, Computer-Assisted Male Radionuclide Imaging Humans Diagnosis, Computer-Assisted Whole Body Imaging Neural Networks, Computer Bone Neoplasms Machine Learning Prostatic Neoplasms Software
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Artificial intelligence for interpretation of segments of whole body MRI in CNO: pilot study comparing radiologists versus machine learning algorithm.

Pediatric rheumatology online journal Jun 9, 2020
BACKGROUND: To initiate the development of a machine learning algorithm capable of comparing segments of pre and post pamidronate whole body MRI scans to assess treatment response and to compare the results of this algorithm with the analysis of a pa...
Tibia Bone Density Conservation Agents Femur Whole Body Imaging Osteitis Pamidronate Magnetic Resonance Imaging Chronic Disease Radiologists Image Interpretation, Computer-Assisted Artificial Intelligence Pilot Projects Machine Learning Adolescent Sensitivity and Specificity Treatment Outcome Disease Progression Support Vector Machine Humans
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Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

Scientific reports May 8, 2020
The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whole-body planar scans (RxWBSs) is important in tracking the progression of the metastatic lymph nodes (mLNs) of patients with papillary thyroid cancer (...
Image Processing, Computer-Assisted Lymphatic Metastasis Iodine Radioisotopes Automation Humans Single Photon Emission Computed Tomography Computed Tomography Retrospective Studies Whole Body Imaging Deep Learning Ablation Techniques Thyroid Neoplasms
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Semi-supervised labelling of the femur in a whole-body post-mortem CT database using deep learning.

Computers in biology and medicine May 6, 2020
A deep learning pipeline was developed and used to localize and classify a variety of implants in the femur contained in whole-body post-mortem computed tomography (PMCT) scans. The results provide a proof-of-principle approach for labelling content ...
Deep Learning Autopsy Femur Whole Body Imaging Tomography, X-Ray Computed
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