AI-segmentation… SEQUOIA 8 Feb 202413 Feb 2024 automated multiclass SEgmentation, QUantification, and visualizatiOn of the dIseased Aorta on hybrid PET/CT SEQUOIA is an automated pipeline for aortic PET/CT studies. First, it segments the ascending aorta, aortic arch,…
AI-PET denoising… Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image Denoising 1 Jan 202413 Feb 2024 Task: Low-dose PET image denoising via a GAN method Description: A hybrid 2D and 3D parameter-transferred Wasserstein GAN PT-WGAN model for low-dose PET image denoising. The model's performance is a…
AI-PET attenuation… Whole Body PET Attenuation Correction Map Synthesizing using 3D Deep Networks 1 Jan 202413 Feb 2024 Task: Whole body attenuation map generation using 3D U-Net generative adversarial networks (GANs) Description: The model is initially trained as a 3D U-Net to learn the mapping from non attenuation…
AI-segmentation… NanoMASK: Nanomedicine Multi-modal AI-based Segmentation for PharmacoKinetics 1 Jan 202413 Feb 2024 Task: Automatic organ and tumor segmentation for nanomedicine pharmacokinetic studies. Description: NanoMASK model is a 3D U-Net adapted deep learning tool capable of rapid, automatic organ segmentation of multimodal imaging…
AI-NeuroImaging… JuST_BrainPET: Juelich Segmentation Tool for Amino Acid PET Brain Tumor Segmentation 1 Jan 202422 Feb 2024 Task: Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET Description: JuST_BrainPET: Juelich Segmentation Tool for Brain Tumor PET is a model trained for metabolic…
AI-multi-modality image fusion… Multi-modal Medical Image Fusion via Multi-dictionary and Truncated Huber Filtering 1 Jan 202413 Feb 2024 Task: Multi-modal medical image fusion Description: The model is comprised of a novel medical image fusion algorithm based on multi-dictionary convolutional sparse representation (CSR) for retaining useful information while achieving…
AI-cardiac… TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction 1 Jan 20249 May 2024 Task: To synthesize a reference late cardiac Rb-82 PET image frame from a set of respective early PET image frames for improved inter-frame registration, motion correction and myocardial blood flow…
AI-NeuroImaging… AI-imputed tau-PET: Synthesizing PET images of tau pathology from cross-modal neuroimaging using deep learning 1 Jan 202423 Feb 2024 Task: To impute tau-PET images from more widely available cross-modality imaging inputs Description: The AI-imputed tau-PET model is a 3D Dense-U-Net Convolutional Neural Network (CNN) that imputes synthetic tau-PET images…
AI-NeuroImaging… brainPETNR: Brain PET Noise Reduction using a Frequency Attention Network 1 Jan 202422 Feb 2024 Task: Denoising of low-activity PET reconstruction of [11C]PiB and [18F]FE-PE2I images in neurodegenerative disorders Description: The brainPETNR framework utilizes a Frequency Attention Network (FAN) model for denoising of low-activity reconstructed brain…
AI-classification… Automated Detection of Focal Cortical Dysplasia With the FCDdetection Model Using Quantitative Multimodal Surface-Based Features 1 Jan 202423 Feb 2024 Task: Detection of Focal Cortical Dysplasia (FCD) lesions by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value. Decription: The FCDdetection model is a neural…
AI-lung cancer… A Bayesian approach to tissue-fraction estimation for oncological PET segmentation 1 Jan 202426 Feb 2024 Task: Semi-automated tissue-fraction estimation-based lesion segmentation from human PET images for quantitative assessments of oncologic diseases. Description: The proposed model implements a novel Bayesian approach to tissue-fraction estimation (TFE) for oncological…
AI-PET synthesis… CycleGAN-QSDL: Quasi-supervised deep learning for super-resolution PET 1 Jan 202419 Feb 2024 Task: Generate synthetic high-resolution PET images from low-resolution PET images Description: QSDL is a quasi-supervised deep learning method, which is a new type of weakly-supervised learning methods, to recover high-resolution…
AI-classification… CGAN-based 18F-Florbetaben PET Data Augmentation for Enhanced Classification of Amyloid-beta distributions 1 Jan 202424 Feb 2024 Task 1: Improve Data Augmentation (DA) of a limited training set of 18F-Florbetaben (18F-FBB) PET images by synthesizing additional realistic 18F-FBB PET images using a Conditional Generative Adversarial Network (CGAN)…
AI-Large Language Models (LLMs)… Automatic Personalized Impression Generation for PET Reports Using Large Language Models(LLMs) 1 Jan 202413 Feb 2024 Task: Automatic Impression Generation for PET Reports Using Large Language Models (LLMs) Description: A collection of twelve open-source language models fine-tuned on a corpus of 37,370 retrospective PET reports were…
AI-outcome prediction… nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation 1 Jan 202420 Feb 2024 nnU-Net (v2) is a deep learning-based segmentation method that automatically configures itself, including preprocessing, network architecture, training and post-processing for any new task in the biomedical domain. The key design…
AI-NeuroImaging… DaT-SPECT-Segmentation: A tissue-fraction estimation-based segmentation framework for quantitative dopamine transporter SPECT 1 Jan 202425 Feb 2024 Task: Fully automated tissue-fraction estimation-based segmentation of the caudate, putamen, and Globus Pallidus (GP) from human brain DaT-SPECT images for quantitative assessments of Parkinson's Disease. Description: The DaT-SPECT-Segmentation model estimates the…
AI-PET denoising… FAN: Frequency Attention Network for Blind Noise Removal in Real Images 1 Jan 202421 Feb 2024 Task: Blind Noise Removal in Real Images Description: The FAN (Frequency Attention Network) model implements a method for blind image denoising that combines frequency domain analysis and attention mechanism, The…
AI-pulses discrimination… DMLLT Detector Pulse Discriminator – A supervised machine learning approach for shape-sensitive detector pulse discrimination in positron annihilation lifetime spectroscopy (PALS) applications 1 Jan 202413 Feb 2024 Task: Detector pulse discrimination in positron annihilation lifetime spectroscopy (PALS) Description: A supervised machine learning (ML) model based on a naive Bayes classification model using a normally distributed likelihood as…
AI-outcome prediction… ICARE: Individual Coefficient Approximation for Risk Estimation model for outcome prediction in head and neck PET/CT 1 Jan 202419 Feb 2024 Task: Recurrence Free Survival (RFS) Prediction in Head and Neck Tumors segmented from 18F-FDG PET/CT images Description: ICARE is a publicly available novel binary-weighted model operating on radiomic features calculated…
AI-PET synthesis… SC-GAN: 3D self-attention conditional GAN with spectral normalization for multi-modal neuroimaging synthesis 1 Jan 202413 Feb 2024 Task: Multimodal (PET & multi-modal MR) 3D medical image synthesis Description: A novel 3D conditional generative adversarial network (GAN) designed and optimized for the application of multimodal 3D neuroimaging synthesis.…
AI-PET reconstruction… Model-based deep learning PET image reconstruction using FBSEM 1 Jan 202413 Feb 2024 Task: Bayesian Iterative PET image reconstruction Description: The model consists of a forward-backward splitting algorithm to integrate deep learning into maximum-a-posteriori (MAP) positron emission tomography (PET) image reconstruction. The MAP…
AI-PET reconstruction… Iterative PET Image Reconstruction Using CNN Representation 1 Jan 202413 Feb 2024 Task: Iterative PET Image reconstruction Description: The model employs a deep residual convolutional neural network to improve PET image quality by using the existing inter-patient information. An innovative feature of…
AI-segmentation… MOOSE 25 Oct 202313 Feb 2024 Multi-organ objective segmentation MOOSE (Multi-organ objective segmentation) is a data-centric AI solution designed to streamline systemic Total-Body research by generating multilabel organ segmentations with high precision. Built on the robust…
AI-Prostate Cancer… Automated mPCa lesion segmentation with self-configuring nnU-Net framework 12 Jun 202320 Feb 2024 An automated segmentation framework based on deep learning for metastatic prostate cancer (mPCa) lesions in whole-body [68Ga]Ga-PSMA-11 PET/CT images for the purpose of extracting patient-level prognostic biomarkers. AI-tool features Disease…