Clinical evaluation of deep learning‐enhanced lymphoma pet ...

Clinical evaluation of deep learning-enhanced lymphoma pet ...

The proposed DL method could facilitate a 50% reduction in PET imaging duration for lymphoma patients, while concurrently preserving image ...

Following enhancement, approximately 76.92% of the samples were deemed to have experienced an improvement in image quality according to the ...

(PDF) Clinical evaluation of deep learning‐enhanced lymphoma pet ...

PDF | Purpose This study aims to evaluate the clinical performance of a deep learning (DL)‐enhanced two‐fold accelerated PET imaging method ...

Clinical evaluation of deep learning‐enhanced lymphoma pet ...

The proposed DL method could facilitate a 50% reduction in PET imaging duration for lymphoma patients, while concurrently preserving image quality and ...

Evaluation of Semiautomatic and Deep Learning–Based Fully ...

Towards enhanced PET quantification in clinical oncology. Br J ... PET/CT in Patients with Follicular Lymphoma. Nucl Med Mol Imaging ...

Evaluation of Deep Learning Based PET Image Enhancement ...

Evaluation metrics included image quality, diagnostic confidence, and intra-reader repeatability test. The lymphoma staging was evaluated using ...

Clinical Evaluation of Deep Learning for Improving PET Image Quality

The CNNd images also yielded better lesion detectability in the noisiest images - for example, at 1 million true counts, average TPR and FNR ...

Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in ...

Deep learning accurately distinguishes between [ 18 F]FDG-PET-CT scans of lymphoma patients with and without hypermetabolic tumour sites.

An artificial intelligence method using FDG PET to predict treatment ...

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to ...

Validation of Deep Learning–based Augmentation for Reduced 18 F ...

CNN enhancement of PET/MRI scans may enable 50% 18 F-FDG dose reduction with correct treatment response assessment of children and young adults with lymphoma.

Clinical Utility of PET/CT in Lymphoma | AJR

The relatively recent integration of PET/CT into routine oncologic imaging has further improved baseline staging and facilitated functional evaluation of ...

(PDF) Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up ...

Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using F-FDG PET/CT Imaging: Contribution of Artificial Intelligence and Radiomics ...

Application of machine learning in the management of lymphoma

In the past decade, digitization of medical records and multiomics data analysis in lymphoma has led to the accessibility of ...

Empowering PET: harnessing deep learning for improved clinical ...

This review aims to take a journey into the transformative impact of artificial intelligence (AI) on positron emission tomography (PET) ...

Weakly supervised deep learning for determining the prognostic ...

... better than conventional clinical parameters and other PET-related ... CT using deep learning in patients with non-small-cell lung cancer.

Role of Artificial Intelligence in PET/CT Imaging for Management of ...

In medical imaging, AI systems can further facilitate many aspects such as clinical decision-making, enhance image acquisition, quality assessment, and post- ...

Performance of a deep learning enhancement method applied to ...

Patient characteristics and clinical indications for the [18F]FDG PET/CT imaging are shown in Table 1. We identified altogether 252 VOIs: 104 lesion VOIs (at ...

Validation of Deep Learning–based Augmentation for Reduced 18F ...

CNN enhancement of PET/MRI scans may enable 50% 18 F-FDG dose reduction with correct treatment response assessment of children and young adults with lymphoma.

Low-count whole-body PET with deep learning in a multicenter and ...

We hypothesize that deep-learning-enhanced fourfold reduced-count PET is noninferior to current standard-dose FDG PET for clinical evaluation ...

Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using ...

A predictive machine learning model was developed using 18F-FDG PET radiomics and clinical data for 113 classical Hodgkin lymphoma patients, identifying high- ...