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Crosslisted article(s) found for cs.SE. https://arxiv.org/list/cs.SE/new
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- KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Commu...
Bhaskar Mangal, Ashutosh Bhatia, Yashvardhan Sharma, Kamlesh Tiwari, Rashmi Verma

Advancing Positron Emission Tomography Image Quantification: Artificial Intelligence-Driven Methods, Clinical Challenges, and Emerging Opportunities in Long-Axial Field-of-View Positron Emission Tomography/Computed Tomography Imaging
Fereshteh Yousefirizi, Movindu Dassanayake, Alejandro Lopez, Andrew Reader, Gary J. R. Cook, Clemens Mingels, Arman Rahmim, Robert Seifert, Ian Alberts

Advancing Positron Emission Tomography Image Quantification: Artificial Intelligence-Driven Methods, Clinical Challenges, and Emerging Opportunities in Long-Axial Field-of-View Positron Emission Tomography/Computed Tomography Imaging
MTV is increasingly recognized as an accurate estimate of disease burden, which has prognostic value, but its implementation has been hindered by the time-consuming need for manual segmentation of images. Automated quantitation using AI-driven approaches is promising. AI-driven automated quantification significantly reduces labor-intensive manual segmentation, improving consistency, reproducibility, and feasibility for routine clinical practice. AI-enhanced radiomics provides comprehensive char…

KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Communication
Bhaskar Mangal, Ashutosh Bhatia, Yashvardhan Sharma, Kamlesh Tiwari, Rashmi Verma
https://arxiv.org/abs/2510.01961

KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Communication
The communication of technical insight in scientific manuscripts often relies on ad-hoc formatting choices, resulting in inconsistent visual emphasis and limited portability across document classes. This paper introduces ktbox, a modular LaTeX framework that unifies semantic color palettes, structured highlight boxes, taxonomy trees, and author metadata utilities into a coherent system for scholarly writing. The framework is distributed as a set of lightweight, namespaced components: ktcolor.st…

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🎵 Layered Presence
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AI's energy demands are driving fossil fuel investment, as energy needs for AI training and data centers are poorly matched with the patterns of solar and wind (Financial Times)

The #AMSAT-UK Colloquium this weekend is streaming live on https://www.youtube.com/live/yk6zI9Pbrig today and another feed tomorrow - see https://amsat-uk.org/2025/10/03/live-stream-of-amsat-uk-colloquium-talks/ for details.

AI-Guided PET Image Reconstruction and Multi-Tracer Imaging: Novel Methods, Challenges, and Opportunities
Movindu Dassanayake, Alejandro Lopez, Andrew Reader, Gary J. R. Cook, Clemens Mingels, Arman Rahmim, Robert Seifert, Ian Alberts, Fereshteh Yousefirizi
https://arxiv.org/abs/2509.00304

AI-Guided PET Image Reconstruction and Multi-Tracer Imaging: Novel Methods, Challenges, and Opportunities
LAFOV PET/CT has the potential to unlock new applications such as ultra-low dose PET/CT imaging, multiplexed imaging, for biomarker development and for faster AI-driven reconstruction, but further work is required before these can be deployed in clinical routine. LAFOV PET/CT has unrivalled sensitivity but has a spatial resolution of an equivalent scanner with a shorter axial field of view. AI approaches are increasingly explored as potential avenues to enhance image resolution.