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A unique sample independent 3D self calibration methodology is tested on a unique optical coherence tomography and multi-spectral scanning laser ophthalmoscope (OCT-SLO) hybrid system. Operators visual cognition is replaced by computer…

Medical Physics · Physics 2024-08-08 Mayank Goswami

Laser cooled atoms are central to modern precision measurements. They are also increasingly important as an enabling technology for experimental cavity quantum electrodynamics, quantum information processing and matter wave interferometry.…

We describe and experimentally implement a single-ion local thermometry technique with absolute sensitivity adaptable to all laser-cooled atomic ion species. The technique is based on the velocity-dependent spectral shape of a quasi-dark…

Atomic Physics · Physics 2019-02-20 Vincent Tugayé , Jean-Pierre Likforman , Samuel Guibal , Luca Guidoni

Artificial intelligence (AI) is increasingly being utilized to optimize magnetic resonance imaging (MRI) protocols. Given that image details are critical for diagnostic accuracy, optimizing MRI acquisition protocols is essential for…

Machine Learning · Computer Science 2025-02-05 Alice Vian , Diego Andre Eifer , Mauricio Anes , Guilherme Ribeiro Garcia , Mariana Recamonde-Mendoza

Scanning Transmission Electron Microscopy (STEM) enables the observation of atomic arrangements at sub-angstrom resolution, allowing for atomically resolved analysis of the physical and chemical properties of materials. However, due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hesong Li , Ziqi Wu , Ruiwen Shao , Tao Zhang , Ying Fu

This work proposes an evolutionary computing-based image segmentation approach for analyzing soundness in Additive Friction Stir Deposition (AFSD) processes. Particle Swarm Optimization (PSO) was employed to determine optimal segmentation…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Akshansh Mishra , Eyob Mesele Sefene , Shivraman Thapliyal

Single atom/molecule manipulation with a scanning-tunneling-microscope (STM) tip is an innovative experimental technique of nanoscience. Using STM-tip as an engineering or analytical tool, artificial atomic-scale structures can be…

Materials Science · Physics 2015-06-25 Saw-Wai Hla

There has been an increasing interest in atom probe tomography (APT) to characterise hydrated and biological materials. A major benefit of APT compared to microscopy techniques more commonly used in biology is its combination of outstanding…

Applied Physics · Physics 2023-11-13 Florant Exertier , Levi Tegg , Adam Taylor , Julie M. Cairney , Jing Fu , Ross K. W. Marceau

Atom probe tomography (APT) is routinely used for analyzing property-enhancing particles in the nanometer-size range and below, and plays a prominent role in the analysis of solute clusters. However, the question of how well these small…

Materials Science · Physics 2020-02-25 Frédéric De Geuser , Baptiste Gault

We present a compact, noise-resilient reconstructive spectrometer-on-a-chip that achieves high-resolution hyperspectral imaging across an extended near-infrared (NIR) range up to 1100nm. The device integrates monolithically fabricated…

Optics · Physics 2025-08-26 Ahasan Ahamed , Htet Myat , Amita Rawat , Lisa N McPhillips , M Saif Islam

The brightfield microscope is instrumental in the visual examination of both biological and physical samples at sub-millimeter scales. One key clinical application has been in cancer histopathology, where the microscopic assessment of the…

Computer Vision and Pattern Recognition · Computer Science 2020-06-03 Po-Hsuan Cameron Chen , Krishna Gadepalli , Robert MacDonald , Yun Liu , Kunal Nagpal , Timo Kohlberger , Jeffrey Dean , Greg S. Corrado , Jason D. Hipp , Martin C. Stumpe

Low-temperature scanning probe microscopes (SPMs) are critical for the study of quantum materials and quantum information science. Due to the rising costs of helium, cryogen-free cryostats have become increasingly desirable. However, they…

AtomAI is an open-source software package bridging instrument-specific Python libraries, deep learning, and simulation tools into a single ecosystem. AtomAI allows direct applications of the deep convolutional neural networks for atomic and…

Data Analysis, Statistics and Probability · Physics 2022-12-29 Maxim Ziatdinov , Ayana Ghosh , Tommy Wong , Sergei V. Kalinin

Segment Anything Model (SAM) is an advanced foundational model for image segmentation, which is gradually being applied to remote sensing images (RSIs). Due to the domain gap between RSIs and natural images, traditional methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Nanqing Liu , Xun Xu , Yongyi Su , Haojie Zhang , Heng-Chao Li

For 35 years, {\it ab initio} molecular dynamics (AIMD) has been the method of choice for modeling complex atomistic phenomena from first principles. However, most AIMD applications are limited by computational cost to systems with…

Computational Physics · Physics 2020-09-15 Weile Jia , Han Wang , Mohan Chen , Denghui Lu , Lin Lin , Roberto Car , Weinan E , Linfeng Zhang

Atomic-scale defect detection is shown in scanning tunneling microscopy images of single crystal WSe2 using an ensemble of U-Net-like convolutional neural networks. Standard deep learning test metrics indicated good detection performance…

The realization of large-scale fully controllable quantum systems is an exciting frontier in modern physical science. We use atom-by-atom assembly to implement a novel platform for the deterministic preparation of regular arrays of…

Study Design: This study presents the development of an autonomous AI system for MRI spine pathology detection, trained on a dataset of 2 million MRI spine scans sourced from diverse healthcare facilities across India. The AI system…

Atomic force microscopy (AFM) is a powerful tool to investigate interaction forces at the micro and nanoscale. Cantilever stiffness, dimensions and geometry of the tip can be chosen according to the requirements of the specific application,…

Applied Physics · Physics 2020-07-31 M. Chighizola , L. Puricelli , L. Bellon , A. Podestà

Isolating the features associated with different materials growth conditions is important to facilitate the tuning of these conditions for effective materials growth and characterization. This study presents machine learning models for…

Materials Science · Physics 2024-02-05 Isaiah A. Moses , Wesley F. Reinhart