Specific features of designing a database for neuro-oncological 3D MRI images to be used in training artificial intelligence

The research was aimed at analyzing current approaches to the organization and design methodology of visualization database built on the basis of computer vision. Such approaches are necessary for effective development of diagnostic systems using artificial intelligence (AI). A training data set of high quality is a mandatory prerequisite for that. Material and methods. The paper presents the technology for designing an annotated database (SBT Dataset) that contains about 1000 clinical cases based on the archived data acquired by the Federal Neurosurgical Center, Novosibirsk, Russia including data on patients with astrocytoma, glioblastoma, meningioma, neurinoma, and patients with metastases of somatic tumors. Each case is represented by a preoperative MRI. The Results and Discussion. The dataset was built (SBT Dataset) containing segmented 3D MRI images of 5 types of brain tumors with 991 verified observations. Each case is represented by four MRI sequences T1-WI, T1C (with Gd-contrast), T2-WI and T2-FLAIR with histological and histochemical postoperative confirmation. Tumors segmentation with verification of the tumor core elements boundaries and perifocal edema was approved by two certified experienced neuroradiologists. Conclusion. The database built during the research is comparable in its volume and quality (verification level) with the state-of-the-art databases. The methodological approaches proposed in this paper were focused on designing the high-quality medical computer vision systems. The database was used to create artificial intelligence systems with the “physician assistant” functions for preoperative MRI diagnostics in neurosurgery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

RD50 Status Report 2008 - Radiation hard semiconductor devices for very high luminosity colliders

The objective of the CERN RD50 Collaboration is the development of radiation hard semiconductor detectors for very high luminosity colliders, particularly to face the requirements of a possible upgrade scenario of the LHC.This document reports the status of research and main results obtained after the sixth year of activity of the collaboration