Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.

Rationale And Objectives: The RANO-BM criteria, which employ a one-dimensional measurement of the largest diameter, are imperfect due to the fact that the lesion volume is neither isotropic nor homogeneous. Furthermore, this approach is inherently time-consuming. Consequently, in clinical practice, monitoring patients in clinical trials in compliance with the RANO-BM criteria is rarely achieved.

Thermogravimetric analysis and kinetic modeling of the pyrolysis of different biomass types by means of model-fitting, model-free and network modeling approaches.

This work aims at comparing the ability of 7 modeling approaches to simulate the pyrolysis kinetics of spruce wood, wheat straw, swine manure, miscanthus and switchgrass. Measurements were taken using a thermogravimetric analyzer (TGA) with 4 heating rates comprised between 5 and 30 K min. The obtained results were processed using 3 isoconversional methods (Kissinger-Akahira-Sunose (KAS), Ozawa-Flynn-Wall (OFW) and Friedman), 1-step and 3-step Kissinger models, as well as an advanced fitting method recently proposed by Bondarchuk et al.

Artificial intelligence solution to accelerate the acquisition of MRI images: Impact on the therapeutic care in oncology in radiology and radiotherapy departments.

Purpose: MRI is essential in the management of brain tumours. However, long waiting times reduce patient accessibility. Reducing acquisition time could improve access but at the cost of spatial resolution and diagnostic quality.

Kinetic Modeling of the Devolatilization of Pulverized Coal, Poplar Wood, and Their Blends in a Thermogravimetric Analyzer and a Flat Flame Reactor.

Devolatilization kinetics of coal, poplar wood, and blends containing 10 and 20 wt % of biomass were characterized. Measurements were carried out under inert atmosphere with heating rates between 10 K min and ∼10 K s using a thermogravimetric analyzer (TGA) and a flat flame reactor (FFR). Measured data were simulated using the chemical percolation devolatilization (CPD) model and a global kinetic scheme based on two competitive reactions integrating a refined differential reaction model.

Thermogravimetric Analysis and Kinetic Modeling of the AAEM-Catalyzed Pyrolysis of Woody Biomass.

This work analyzes the catalytic effects induced by alkali and alkaline earth metals (AAEMs) on pyrolysis kinetics. To this end, thermogravimetric analyses (TGA) were carried out with raw beech wood and samples impregnated with NaCl, KCl and MgCl at four heating rates (5, 10, 15 and 30 °C/min). Obtained results showed that AAEM compounds promote the decomposition of biomass by reducing the initial and peak pyrolysis temperatures.