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A Stochastic Minimum-Norm Approach to Image and Texture Interpolation

Related publications (32)

A single-cell-based characterization of mammalian adipose stem and progenitor cell heterogeneity and function

White adipose tissue (WAT) is a cellularly heterogeneous endocrine organ that not only serves as a reservoir for storing and releasing energy but also actively participates in metabolic homeostasis. Given the current rise in obesity and its associated como ...

EPFL2023

Cross-anatomical single-cell definition and characterization of human adipose progenitor niche

Radiana Ferrero

Adipose tissue is a key metabolic and highly-dynamic organ whose dysregulation may cause clinical conditions of concern such as obesity and lipodystrophy. Its function varies based on the anatomy, in fact, visceral adipose tissue expansion carries a greate ...

EPFL2023

Engineered substrates incapable of induction of chondrogenic differentiation compared to the chondrocyte imprinted substrates

Philippe Renaud, Shahin Bonakdar, Leila Montazeri, Zahrasadat Ghazali

It is well established that surface topography can affect cell functions. However, finding a reproducible and reliable method for regulating stem cell behavior is still under investigation. It has been shown that cell imprinted substrates contain micro- an ...

IOP Publishing Ltd2023

Countering T cell exhaustion and senescence for enhanced adoptive T cell therapies against solid tumors

Yang Zhao

CAR-T cell therapy has shown remarkable success in treating hematopoietic malignancies, but its efficacy in solid tumors is limited by T cell dysfunction, including exhaustion and senescence. In this study, we designed metabolically armored CAR-T cells to ...

EPFL2023

Region Extraction in Mesh Intersection

Annalisa Buffa, Pablo Antolin Sanchez, Emiliano Cirillo

Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...

2023

Comparison of Three Imputation Methods for Groundwater Level Timeseries

Andrea Rinaldo

This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead bot ...

MDPI2023

Automated Dual-Mode Cell Monitoring To Simultaneously Explore Calcium Dynamics and Contraction-Relaxation Kinetics within Drug-Treated Stem Cell-Derived Cardiomyocytes

Gerardo Turcatti, Pierre Marquet, Benjamin Rappaz, Bokyoung Kim

This manuscript proposes a new dual-mode cell imaging system for studying the relationships between calcium dynamics and the contractility process of cardiomyocytes derived from human-induced pluripotent stem cells. Practically, this dual-mode cell imaging ...

AMER CHEMICAL SOC2023

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Max Stieber, Martin Weigert, Benjamin Tobias Gallusser

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Springer International Publishing Ag2023

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

2023

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Seyedbehzad Bozorgtabar, Devavrat Tomar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

IEEE2023