Search results for "COMPRESSION"

Can pressure-induced cell inactivation be related to cell volume compression? A case study for Saccharomyces cerevisiae

2013

In this paper, emphasis has been put on the relationship between volume compression and cell inactivation for the Saccharomyces cerevisiae strain CBS 1171 submitted to high hydrostatic pressure treatments. The influence of cell dehydration on pressure inactivation was first investigated. Inactivation was found to be strongly limited, or even completely prevented for cells with a water content of 60% w/w or below. Moreover, the volume compression undergone by a single yeast cell was assessed as a function of pressure and hydration conditions using a high-pressure setup for pressure-volume-temperature measurements. Direct measurements of volume compression were performed on cell pellets after…

Einstein Studies, volume 11: A retrospective review

2008

Collected works, volume 6

2006

Probing the low-temperature chemistry of ethanol via the addition of dimethyl ether

2018

Considering the importance of ethanol (EtOH) as an engine fuel and a key component of surrogate fuels, the further understanding of its auto-ignition and oxidation characteristics at engine-relevant conditions (high pressures and low temperatures) is still necessary. However, it remains difficult to measure ignition delay times for ethanol at temperatures below 850 K with currently available facilities including shock tube and rapid compression machine due to its low reactivity. Considering the success of our recent study of toluene oxidation under similar conditions [38], dimethyl ether (DME) has been selected as a radical initiator to explore the low-temperature reactivity of ethanol. In …

Comparative study of multi-2D, Full 3D and hybrid strategies for multi/hyperspectral image compression

2009

In this paper, we investigate appropriate strategies for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression strategy and two different implementations of 3D strategies (Full 3D and hybrid). All strategies are combined with a PCA decorrelation stage to optimize performance. For multi-2D and hybrid strategies, we propose a weighted version of PCA. Finally, for consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR. The results are significant and show the weaknesses and strengths of each strategy.

The impact of irreversible image data compression on post-processing algorithms in computed tomography

2020

PURPOSE: We aimed to evaluate the influence of irreversible image compression at varying levels on image post-processing algorithms (3D volume rendering of angiographs, computer-assisted detection of lung nodules, segmentation and volumetry of liver lesions, and automated evaluation of functional cardiac imaging) in computed tomography (CT). METHODS: Uncompressed CT image data (30 angiographs of the lower limbs, 38 lung exams, 20 liver exams and 30 cardiac exams) were anonymized and subsequently compressed using the JPEG2000 algorithm with compression ratios of 8:1, 10:1, and 15:1. Volume renderings of CT angiographies obtained from compressed and uncompressed data were compared using objec…

Low Complexity Image Compression using Pruned 8-point DCT Approximation in Wireless Visual Sensor Networks

2017

International audience; Since the transmission of the uncompressed image in the context of wireless visual sensor networks (WVSNs) consumes less energy than transmitting the compressed image, developing energy-aware compression algorithms are mandatory to extend the camera node's lifetime and thereby the whole network lifetime. The present paper studies a low-complexity image compression algorithm in the context of WVSNs. This algorithm consists of applying a pruning approach on a DCT approximation transform. The scheme is investigated in terms of computation cycles, processing time, energy consumption and image quality. Experimental works are conducted using the Atmel Atmega128 processor o…

Projection-based improvement of 3D reconstructions from motion-impaired dental cone beam CT data.

2019

Purpose Computed tomography (CT) and, in particular, cone beam CT (CBCT) have been increasingly used as a diagnostic tool in recent years. Patient motion during acquisition is common in CBCT due to long scan times. This results in degraded image quality and may potentially increase the number of retakes. Our aim was to develop a marker-free iterative motion correction algorithm that works on the projection images and is suitable for local tomography. Methods We present an iterative motion correction algorithm that allows the patient's motion to be detected and taken into account during reconstruction. The core of our method is a fast GPU-accelerated three-dimensional reconstruction algorith…

Solid-State Pyrolyses of Metal Phthalocyanines: A Simple Approach towards Nitrogen-Doped CNTs and Metal/Carbon Nanocables

2006

Solid-state pyrolysis of organometallic precursors has emerged as an alternative method for preparing carbon nanostructures such as carbon nanotubes (CNT) and carbon anions. The morphology of the tubes can be controlled by the nature of the precursors and the pyrolysis procedures, and micrometer long nanotubes, composed of metal carbide wires encased in a graphitic sheath. Cobalt phthalocyanine (CoPc) as well as iron phthalocyanine were pyrolyzed at different temperatures to obtain CNTs. HRTEM and energy-dispersion X-Ray analysis disclosed that the core consisted of long, iron-containing single crystals and that the core was fully surrounded by crystallized graphic carbon. Iron-filled carbo…

A 3D deep learning approach based on Shape Prior for automatic segmentation of myocardial diseases

2020

Accurate three-dimensional (3D) cardiac segmentation from late gadolinium enhancement (LGE)-MRI plays a critical role in designing a structure of reference for diagnosing many cardiac pathologies such as ischemia, myocarditis and myocardial infarction. This segmentation is however still a non-trivial task, due to the motion artifacts during acquisition, and heterogeneous intensity distributions. In this study, we develop a fully 3D automated model based on deep neural networks (DNN) for LGE-MRI myocardial pathologies (scar and No-reflow tissues) segmentation in a new expert annotated dataset. Considering that damaged tissue constitutes a small area of the whole LGE-MRI, we concentrated on m…