98%
921
2 minutes
20
Biological visions have inspired the development of artificial vision systems with diverse visual functional traits, however, the detected wavelength is only in visible light between 0.4 and 0.78 μm, restricting their applications. Snakes generate a thermal image of animals due to pit organs for detecting and converting infrared, allowing them to accurately target predators or prey even under darkness. Inspired by natural infrared visualized snakes, we propose artificial vision systems with CMOS sensors-integrated upconverters to break visible light limitations to realize 3840 × 2160 ultra-high-resolution short-wave infrared (SWIR) and mid-wave infrared (MWIR) visualization imaging for the first time. Through colloidal quantum dot barrier heterojunction architecture design of infrared detecting units and the introduction of co-hosted emitting units, the luminance and upconversion efficiency reach up to 6388.09 cd m and 6.41% for SWIR, 1311.64 cd m and 4.06% for MWIR at room temperature. Our artificial vision systems broaden a wide spectrum of applications within infrared, such as night vision, agricultural science, and industry inspection, marking a significant advance in bioartificial vision.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12368111 | PMC |
http://dx.doi.org/10.1038/s41377-025-02001-x | DOI Listing |
Front Digit Health
August 2025
Department of Ophthalmology, Stanford University, Palo Alto, CA, United States.
Introduction: Vision language models (VLMs) combine image analysis capabilities with large language models (LLMs). Because of their multimodal capabilities, VLMs offer a clinical advantage over image classification models for the diagnosis of optic disc swelling by allowing a consideration of clinical context. In this study, we compare the performance of non-specialty-trained VLMs with different prompts in the classification of optic disc swelling on fundus photographs.
View Article and Find Full Text PDFJ Biomed Opt
September 2025
Leibniz University Hannover, Hannover Centre for Optical Technologies, Hannover, Germany.
Significance: Melanoma's rising incidence demands automatable high-throughput approaches for early detection such as total body scanners, integrated with computer-aided diagnosis. High-quality input data is necessary to improve diagnostic accuracy and reliability.
Aim: This work aims to develop a high-resolution optical skin imaging module and the software for acquiring and processing raw image data into high-resolution dermoscopic images using a focus stacking approach.
Patterns (N Y)
July 2025
L3S Research Center, Leibniz University Hannover, Hannover, Germany.
OpenML is an open-source platform that democratizes machine-learning evaluation by enabling anyone to share datasets in uniform standards, define precise machine-learning tasks, and automatically share detailed workflows and model evaluations. More than just a platform, OpenML fosters a collaborative ecosystem where scientists create new tools, launch initiatives, and establish standards to advance machine learning. Over the past decade, OpenML has inspired over 1,500 publications across diverse fields, from scientists releasing new datasets and benchmarking new models to educators teaching reproducible science.
View Article and Find Full Text PDFCancer Med
September 2025
Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia.
Background: Patients with clear cell renal cell carcinoma (ccRCC) often undergo organ resection, with treatment strategies based on recurrence risk. Current metastatic potential assessments rely on the WHO/ISUP grading system, which is subject to interobserver variability.
Methods: We developed an artificial intelligence (AI) model to classify cells according to contemporary grading rules and evaluated the prognostic significance of tumor cell profiles, particularly focusing on cells with prominent nucleoli.
JMIR Form Res
September 2025
Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangdong Provincial Geriatrics Institute, No. 106, Zhongshaner Rd, Guangzhou, 510080, China, 86 15920151904.
Background: Point-of-care ultrasonography has become a valuable tool for assessing diaphragmatic function in critically ill patients receiving invasive mechanical ventilation. However, conventional diaphragm ultrasound assessment remains highly operator-dependent and subjective. Previous research introduced automatic measurement of diaphragmatic excursion and velocity using 2D speckle-tracking technology.
View Article and Find Full Text PDF