Nuclear Medicine

Non-invasively Discriminating the Pathological Subtypes of Non-small Cell Lung Cancer with Pretreatment F-FDG PET/CT Using Deep Learning.

RATIONALE AND OBJECTIVES: To develop an end-to-end deep learning (DL) model for non-invasively predi...

Deep learning to automate SPECT MPI myocardial reorientation.

Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout.

. Radiation therapy for head and neck (H&N) cancer relies on accurate segmentation of the primary tu...

A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.

Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPEC...

Need for objective task-based evaluation of deep learning-based denoising methods: A study in the context of myocardial perfusion SPECT.

BACKGROUND: Artificial intelligence-based methods have generated substantial interest in nuclear med...

The Past, Present, and Future Role of Artificial Intelligence in Ventilation/Perfusion Scintigraphy: A Systematic Review.

Ventilation-perfusion (V/Q) lung scans constitute one of the oldest nuclear medicine procedures, rem...

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization.

The objective is to assess the performance of seven semiautomatic and two fully automatic segmentati...

Can Deep Learning Detect Incidental Abnormal Cardiac Uptake Related to Amyloidosis on Routine Bone Scintigraphy?

Deep Learning on Bone Scintigraphy to Detect Abnormal Cardiac Uptake at Risk of Cardiac Amyloidosis.

BACKGROUND: Cardiac uptake on technetium-99m whole-body scintigraphy (WBS) is almost pathognomonic o...

Acquisition time reduction in pediatric Tc-DMSA planar imaging using deep learning.

PURPOSE: Given the potential risk of motion artifacts, acquisition time reduction is desirable in pe...

Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human observer performance.

PURPOSE: Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in diagnosing ...

Clinical application of AI-based PET images in oncological patients.

Based on the advantages of revealing the functional status and molecular expression of tumor cells, ...

PET scatter estimation using deep learning U-Net architecture.

Positron emission tomography (PET) image reconstruction needs to be corrected for scatter in order t...

Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

BACKGROUND: For PET/CT, the CT transmission data are used to correct the PET emission data for atten...

Successful all robotic-assisted excision of highly malignant mediastinal neuroblastoma in a toddler: A case report.

An otherwise well 28-month-old girl presented with fever/left thigh pain. Computed tomography identi...

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma.

Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-en...

Automatic reorientation by deep learning to generate short-axis SPECT myocardial perfusion images.

BACKGROUND: Single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) can...

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.

 Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate...

Deep learning based identification of bone scintigraphies containing metastatic bone disease foci.

PURPOSE: Metastatic bone disease (MBD) is the most common form of metastases, most frequently derivi...

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application.

. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). ...

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for sel...