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Contrastive learning has been proved to be a promising technique for image-level representation learning from unlabeled data. Many existing works have demonstrated improved results by applying contrastive learning in classification and…

Cardiac segmentation of atriums, ventricles, and myocardium in computed tomography (CT) images is an important first-line task for presymptomatic cardiovascular disease diagnosis. In several recent studies, deep learning models have shown…

The Apodized Pupil Lyot Coronagraph (APLC) is a diffraction suppression system installed in the recently deployed instruments Palomar/P1640, Gemini/GPI, and VLT/SPHERE to allow direct imaging and spectroscopy of circumstellar environments.…

The segmentation and classification of cardiac magnetic resonance imaging are critical for diagnosing heart conditions, yet current approaches face challenges in accuracy and generalizability. In this study, we aim to further advance the…

METIS will be among the first generation of scientific instruments on the E-ELT. Focusing on highest angular resolution and high spectral resolution, METIS will provide diffraction limited imaging and coronagraphy from 3-14um over an…

Deep learning approaches to the segmentation of magnetic resonance images have shown significant promise in automating the quantitative analysis of brain images. However, a continuing challenge has been its sensitivity to the variability of…

Existing Electric Field Conjugation (EFC) methods are not suited for treating small polarization effects, referred to here as cross polarization. EFC utilizes a deformable mirror (DM) to nullify the electric fields from the host star within…

Image-guided adaptive lung radiotherapy requires accurate tumor and organs segmentation from during treatment cone-beam CT (CBCT) images. Thoracic CBCTs are hard to segment because of low soft-tissue contrast, imaging artifacts, respiratory…

Semi-supervised learning (SSL) is a promising machine learning paradigm to address the issue of label scarcity in medical imaging. SSL methods were originally developed in image classification. The state-of-the-art SSL methods in image…

Leveraging the disparity information from both left and right views is crucial for stereo disparity estimation. Left-right consistency check is an effective way to enhance the disparity estimation by referring to the information from the…

A vortex coronagraph is now available for high contrast observations with the Keck/NIRC2 instrument at L band. Reaching the optimal performance of the coronagraph requires fine control of the wavefront incident on the phase mask. In…

Maintaining wavefront stability while directly imaging exoplanets over long exposure times is an ongoing problem in the field of high-contrast imaging. Robust and efficient high-order wavefront sensing and control systems are required for…

Space-based stellar coronagraph instruments aim to directly image exoplanets that are a fraction of an arcsecond separation and ten billion times fainter than their host star. To achieve this, one or more deformable mirrors (DMs) are used…

The Segment Anything Model (SAM) has garnered significant attention for its versatile segmentation abilities and intuitive prompt-based interface. However, its application in medical imaging presents challenges, requiring either substantial…

The second-generation instrument SPHERE, dedicated to high-contrast imaging, will soon be in operation on the European Very Large Telescope. Such an instrument relies on an extreme adaptive optics system coupled with a coronagraph that…

Three-dimensional (3D) semi-quantitative grading of pathological features in articular cartilage (AC) offers significant improvements in basic research of osteoarthritis (OA). We have earlier developed the 3D protocol for imaging of AC and…

With the popularity of foundational models, parameter efficient fine tuning has become the defacto approach to leverage pretrained models to perform downstream tasks. Taking inspiration from recent advances in large language models, Visual…

In this study, we perform a statistical analysis of the radar cross section (RCS) for various test targets in an indoor factory at \(25\)-\(28\) GHz, with the goal of formulating parameters that may be used for target identification and…

Stellar coronagraph performance is highly sensitive to optical aberrations. In order to effectively suppress starlight for exoplanet imaging applications, low-order wavefront aberrations entering a coronagraph such as tip-tilt, defocus and…

Kernel phase is a method to interpret stellar point source images by considering their formation as the analytical result of an interferometric process. Using Fourier formalism, this method allows for observing planetary companions around…