What is the best data augmentation for 3D brain tumor segmentation?

Training segmentation networks requires large annotated datasets, which in medical imaging can be hard to obtain. Despite this fact, data augmentation has in our opinion not been fully explored for brain tumor segmentation. In this project we apply different types of data augmentation (flipping, rotation, scaling, brightness adjustment, elastic deformation) when training a standard 3D U-Net, and demonstrate that augmentation significantly improves the network's performance in many cases. Our conclusion is that brightness augmentation and elastic deformation work best, and that combinations of different augmentation techniques do not provide further improvement compared to only using one augmentation technique. Our code is available at https://github.com/mdciri/3D-augmentation-techniques

Vox2Vox: 3D-GAN for Brain Tumour Segmentation

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histological sub-regions, i.e., peritumoral edema, necrotic core, enhancing and non-enhancing tumour core. Although brain tumours can easily be detected using multi-modal MRI, accurate tumor segmentation is a challenging task. Hence, using the data provided by the BraTS Challenge 2020, we propose a 3D volume-to-volume Generative Adversarial Network for segmentation of brain tumours. The model, called Vox2Vox, generates realistic segmentation outputs from multi-channel 3D MR images, segmenting the whole, core and enhancing tumor with mean values of 87.20%, 81.14%, and 78.67% as dice scores and 6.44mm, 24.36mm, and 18.95mm for Hausdorff distance 95 percentile for the BraTS testing set after ensembling 10 Vox2Vox models obtained with a 10-fold cross-validation

KubeNow: A Cloud Agnostic Platform for Microservice-Oriented Applications

KubeNow is a platform for rapid and continuous deployment of microservice-based applications over cloud infrastructure. Within the field of software engineering, the microservice-based architecture is a methodology in which complex applications are divided into smaller, more narrow services. These services are independently deployable and compatible with each other like building blocks. These blocks can be combined in multiple ways, according to specific use cases. Microservices are designed around a few concepts: they offer a minimal and complete set of features, they are portable and platform independent, they are accessible through language agnostic APIs and they are encouraged to use standard data formats. These characteristics promote separation of concerns, isolation and interoperability, while coupling nicely with test-driven development. Among many others, some well-known companies that build their software around microservices are: Google, Amazon, PayPal Holdings Inc. and Netflix [11]

On the hydrothermal depolymerisation of kraft lignin using glycerol as a capping agent

Depolymerisation of kraft lignin under hydrothermal conditions was investigated at short residence times (1–12\ua0min) with glycerol being used as a capping agent. The weight average molecular weight (M w) of the products decreased within the first minute of residence time, with the inter-unit ether linkages breaking accordingly. Furthermore, the M w of the product fractions decreased at increasing residence times, while the char yield increased. Short residence times thus appear to be beneficial for mitigating the formation of char. Also, addition of NaOH reduced the yield of char. Although the addition of glycerol caused a decrease in the M w of the products, it seemed to increase the yield of char and therefore might not be a suitable capping agent for kraft lignin depolymerisation

Towards understanding kraft lignin depolymerisation under hydrothermal conditions

Kraft lignin depolymerisation using hydrothermal liquefaction suffers from the formation of char, resulting in a decreased product yield as well as causing operational problems. While this may be mitigated by the addition of capping agents such as phenol and isopropanol, other reaction parameters, for example reaction time and temperature, are also important for the product yields. In this work, the effect of short reaction times on the hydrothermal liquefaction of kraft lignin in an alkaline water and isopropanol mixture was investigated at 1-12 min and 290 \ub0C. The results show that there were swift initial reactions: the major ether bonds in the lignin were broken within the first minute of reaction, and the molecular weight of all product fractions was halved at the very least. Longer reaction times, however, do not cause as pronounced structural changes as the initial reaction, indicating that a recalcitrant carbon-carbon skeleton remained in the products. Nevertheless, the yields of both char and monomers increased slowly with increasing reaction time. The swift initial depolymerising reactions were therefore followed by slower repolymerisation as well as a slow formation of monomers and dimers, which calls for careful tuning of the reaction time

Self-Assembly in Physical Autonomous Robots: the Evolutionary Robotics Approach

info:eu-repo/semantics/publishe