Nuclear Medicine

An attention-guided multimodal deep learning framework by integrating CT-PET imaging and clinical data for lung cancer detection.

The proposed multi-modal deep learning system for lung cancer diagnosis and characterisation uses structural (CT), functional (PET), and clinical (EHR) data. The heterogeneous information fusion technique uses a clinical data encoder, an attention-based fusion mechanism, and a convolutional neural network backbone for image feature extraction. Multi-task learning combines tumor categorization and ...

Nonlinear hydrothermal associations between coupled landscape ecological risk and resilience in a major grain-producing region of China.

In major grain-producing regions, hydrothermal processes are critical for regulating ecosystem stability. However, the long-term coupled dynamics between landscape ecological risk (LER) and vegetation-based ecological resilience (ER) remain inadequately quantified, particularly in intensively managed agro-wetland landscapes. Here, we developed a Coupled Risk and Resilience Integration (CRRI) frame...

Tracer-agnostic diffusion model-based CT-free attenuation correction for brain PET: Comprehensive evaluation across 14 tracers.

OBJECTIVE: Accurate attenuation correction (AC) is critical in quantitative brain PET imaging. Conventional CT-based AC methods increase radiation exp...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

The optimal SVM model from multi-model comparison outperforms conventional criteria in preoperative prediction of ovarian cancer residual disease.

OBJECTIVE: To develop an interpretable artificial intelligence (AI)-based machine learning model integrating 18F-fluorodeoxyglucose positron emission ...

On the utility of ChatGPT in conducting a literature review on deep learning for dopamine transporter SPECT with [¹²³I]ioflupane.

AIM: This study evaluated ChatGPT (GPT-5.2) for drafting a review paper on deep learning in dopamine transporter (DAT)-SPECT with [¹²³I]ioflupane. MET...

Multimodal PET/CT-based PD-L1 status prediction in lung cancer via semi-supervised and unsupervised deep learning.

Deep learning (DL) techniques have been applied in lung cancer screening, assessing drug effectiveness, and enhancing prognosis prediction. Within thi...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility fo...

[Current status and progress of prognostic evaluation in marginal zone lymphoma].

Marginal zone lymphoma (MZL) is an indolent B-cell non-Hodgkin lymphoma with marked heterogeneity. Currently, histological subtype, clinical stage, bi...

Unveiling the sensing mechanism of a Nile Red-naphthoquinone H₂S fluorescent probe: theoretical calculation and deep learning prediction.

Hydrogen sulfide (H₂S) is a vital endogenous gasotransmitter implicated in numerous physiological and pathological processes; thus, its precise detect...

Performance of the Techcyte AI-based image analysis system for coproparasitological diagnosis in clinical stool specimens: a retrospective evaluation study.

UNLABELLED: Coproparasitological stool analysis based on microscopic examination is the reference diagnostic technique routinely performed in clinical...

Denoising of ultra-low-dose 15O positron emission tomography images using deep image prior with anatomical information extracted through magnetic resonance segmentation.

PURPOSE: Recent deep-learning methods can recover standard-dose PET images from low-dose images. However, these methods require a large amount of data...

Accelerating the discovery of industrial PET-degrading enzymes: Evolving paradigms from bioprospecting to computational discovery.

Polyethylene terephthalate (PET) waste remains a major environmental and resource challenge, and enzymatic depolymerization offers a promising route f...

Evaluation of PET/CT Artificial Intelligence Image Reconstructions VS Harmonized Clinical Reconstruction.

BACKGROUND: This study focuses on evaluating how SubtlePET™, an artificial intelligence (AI)-based image enhancement algorithm, produced PET/CT images...

Standardizing PSMA PET/CT reporting in prostate cancer: from structured frameworks to AI-assisted interpretation.

PSMA PET/CT is increasingly used for prostate cancer staging, restaging, treatment selection, and therapy response assessment. In parallel, several in...

Automatic metabolic breast cancer staging using [¹⁸F]FDG PET/CT: comparison with nuclear medicine physician-based and clinical staging.

PURPOSE: This study aimed to evaluate a deep-learning (DL)-based framework to automatically perform breast cancer (BC) metabolic staging on [¹⁸F]FDG P...

RDoC-informed explainable AI as a paradigm for multilevel Alzheimer's disease diagnosis and progression prediction: a systematic review.

Explainable Artificial Intelligence (XAI) is gaining popularity in early diagnosis and monitoring of dementia. Herein, we recommend the incorporation ...

Denoising of 4D dynamic PET images using spatiotemporal regularization with integrated temporal restoration (SPRINTER).

PURPOSE: High-quality 4D dynamic PET imaging is often compromised by noise, especially in low-count frames, which limits clinical utility and quantita...

Explainable AI for MRI Alzheimer's disease classification: A comparative analysis.

We introduce a quantitative pipeline for region-level explanations of an Alzheimer's prediction model using four post hoc explainable AI (XAI) methods...

Risk stratification for reoperation outcomes in recurrent or persistent papillary thyroid carcinoma: development and validation of a machine learning model.

BACKGROUNDS: Reoperation is a key therapeutic strategy for recurrent or persistent papillary thyroid carcinoma (PTC), but its outcomes remain highly h...