Alejandro López-Montes

A Positron Range Correction with Texture Preservation Framework in PET Imaging

Nerea Encina-Baranda, Yifan Zheng, Jorge Cabello, Robert. J. Paneque-Yunta et autres

Positron range (PR) blurring is a fundamental resolution limitation in PET imaging with high-energy positron emitters such as 82Rb, causing contrast loss and spill-out effects across heterogeneous tissue interfaces. We propose PRC-TP, a positron range correction (PRC) framework with explicit texture preservation …

A Positron Range Correction with Texture Preservation Framework in PET Imaging

Nerea Encina-Baranda, Yifan Zheng, Jorge Cabello, Robert. J. Paneque-Yunta et autres

Positron range (PR) blurring is a fundamental resolution limitation in PET imaging with high-energy positron emitters such as 82Rb, causing contrast loss and spill-out effects across heterogeneous tissue interfaces. We propose PRC-TP, a positron range correction (PRC) framework with explicit texture preservation …

es (code pays fourni par la source)

A tissue-informed deep learning-based method for positron range correction in preclinical $$^{68}$$Ga PET imaging

Nerea Encina-Baranda, Robert J. Paneque-Yunta, Javier López‐Rodriguez, Edwin C. Pratt et autres

Positron range (PR) limits spatial resolution and quantitative accuracy in PET imaging, particularly for high-energy positron-emitting radionuclides such as \(^{68}\) Ga. This study proposes a deep learning-based approach using 3D residual encoder-decoder convolutional neural networks (3D RED-CNNs), incorporating tissue-dependent anatomical information through …

es, us, ch (code pays fourni par la source)

A tissue-informed deep learning-based method for positron range correction in preclinical [Formula: see text]Ga PET imaging.

Nerea Encina-Baranda, Robert J. Paneque-Yunta, Javier López‐Rodriguez, Edwin C. Pratt et autres

es, us, ch (code pays fourni par la source)

Phantom-based comparison of image quality in two digital PET/CT systems with different axial fields of view

Khomotso Marlene Legodi, Milani Qebetu, Kaluzi Banda, Pryaska Goorhoo et autres

Abstract Objective. Silicon photomultiplier (SiPM)-based positron emission tomography (PET)/ computed tomography (CT) scanners offer enhanced sensitivity and timing resolution compared with conventional detector designs. This study compared two SiPM PET/CT systems sharing the same technology platform but differing in axial field of …

jp, Afrique du Sud, ch (code pays fourni par la source)

A tissue-informed deep learning-based method for positron range correction in preclinical 68Ga PET imaging.

Nerea Encina-Baranda, Robert J. Paneque-Yunta, Javier López‐Rodriguez, Edwin C. Pratt et autres

Positron range (PR) limits spatial resolution and quantitative accuracy in PET imaging, particularly for high-energy positron-emitting radionuclides like 68Ga. We propose a deep learning method using 3D residual encoder-decoder convolutional neural networks (3D RED-CNNs), incorporating tissue-dependent anatomical information through a u-map-dependent loss …

Artificial Intelligence for Simplified Patient-centered Dosimetry in Radiopharmaceutical Therapies

Alejandro López-Montes, Fereshteh Yousefirizi, Yizhou Chen, Yazdan Salimi et autres

ch, ca (code pays fourni par la source)

DL-Based Method for Positron Range Correction in Clinical PET Imaging

Nerea Encina-Baranda, Yefeng Zheng, Jean Cabello, Alejandro López-Montes et autres

The positron range limits spatial resolution in Positron Emission Tomography (PET), especially for radionuclides like${ }^{68} \text{Ga}$and${ }^{82} \text{Rb}$, which emit high energy positrons with longer tissue ranges compared to${ }^{18} ~\mathrm{F}$or${ }^{13} ~\mathrm{N}$. We propose a deep learning-based PRC method that …

es, us, gb, ch (code pays fourni par la source)

Patient-Specific AI for Generation of 3D Dosimetry Imaging from Two 2D-Planar Measurements

Alejandro López-Montes, Robert Seifert, Andreas Delker, Guido Boening et autres

In this work we explored the use of patient specific reinforced learning to generate 3D activity maps from two 2D planar images (anterior and posterior). The solution of this problem remains unachievable using conventional methodologies and is of particular interest for dosimetry …

ch, de (code pays fourni par la source)

Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies

Alejandro López-Montes, Fereshteh Yousefirizi, Yizhou Chen, Yazdan Salimi et autres

KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutions to the key limitations in …

The Evolution of Artificial Intelligence in Nuclear Medicine

Leonor Lopes, Alejandro López-Montes, Yizhou Chen, Pia Koller et autres

Nuclear medicine has continuously evolved since its beginnings, constantly improving the diagnosis and treatment of various diseases. The integration of artificial intelligence (AI) is one of the latest revolutionizing chapters, promising significant advancements in diagnosis, prognosis, segmentation, image quality enhancement, and theranostics. …

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Deep-PRC: A Positron Range Correction Tool for preclinical and clinical PET/CT images

Nerea Encina-Baranda, Javier López‐Rodriguez, Alejandro López-Montes, Paula Ibáñez et autres

Deep-PRC is a deep learning-based Positron Range Correction (PRC) method for enhancing spatial resolution and accuracy in Positron Emission Tomography (PET) scans using radionuclides with large positron ranges, such as 68Ga. Traditional PRC strategies often increase the noise in the final images …

es, us (code pays fourni par la source)