Biomedical subjects

Xinhua Cao

Publications and source records attributed to Xinhua Cao.

3 recordsLinked to original sources

PubMed2005

A computerized cellular imaging system for high content analysis in Monastrol suppressor screens.

In this paper, we describe a new bioimage informatics system developed for high content screening (HCS) applications with the goal to extract and analyze phenotypic features of hundreds of thousands of mitotic cells simultaneously. The system introduces the algorithm of multi-phenotypic mitotic analysis (MMA) and integrates that with algorithms of correlation analysis and compound clustering used in gene microarray studies. The HCS-MMA system combines different phenotypic information of cellular images obtained from three-channel acquisitions to distinguish and label individual cells at various phases of mitosis. The proposed system can also be used to extract and count the number of cells in each phase in cell-based assay experiments and archive the extracted data into a structured database for more sophisticated statistical and data analysis. To recognize different mitotic phases, binary patterns are set up based on a known biological mitotic spindle model to characterize cellular morphology of actin, microtubules, and DNA. To illustrate its utility, the HCS-MMA system has been applied to screen the quantitative response of 320 different drug compounds in suppressing Monastrol. The results are validated and evaluated by comparing the performance of HCS-MMA with visual analysis, as well as clustering of the drug compounds under evaluation.

Algorithms↗

PubMed2004

A neuroinformatics database system for disease-oriented neuroimaging research.

Clinical databases are continually growing and accruing more patient information. One of the challenges for managing this wealth of data is efficient retrieval and analysis of a broad range of image and non-image patient data from diverse data sources. This article describes the design and implementation of a new class of research data warehouse, neuroinformatics database system (NIDS), which will alleviate these problems for clinicians and researchers studying and treating patients with intractable temporal lobe epilepsy. The NIDS is a secured, multi-tier system that enables the user to gather, proofread, analyze, and store data from multiple underlying sources. In addition to data management, the NIDS provides several key functions including image analysis and processing, free text search of patient reports, construction of general queries, and on-line statistical analysis. The establishment of this integrated research database will serve as a foundation for future hypothesis-driven experiments, which could uncover previously unsuspected correlations and perhaps help to identify new and accurate predictors for image diagnosis.

Biomedical Research↗

PubMed2004

A web-based federated neuroinformatics model for surgical planning and clinical research applications in epilepsy.

There is an increasing need to efficiently share diverse clinical and image data among different clinics, labs, and departments of a medical center enterprise to facilitate better quality care and more effective clinical research. In this paper, we describe a web-based, federated information model as a viable technical solution with applications in medical refractory epilepsy and other neurological disorders. We describe four such online applications developed in a federated system prototype: surgical planning, image analysis, statistical data analysis, and dynamic extraction, transforming, and loading (ETL) of data from a heterogeneous collection of data sources into an epilepsy multimedia data warehouse (EMDW). The federated information system adopts a three-tiered architecture, consisting of a user-interface layer, an application logic layer, and a data service layer. We implemented two complementary federated information technologies, i.e., XML (eXtensible Markup Language) and CORBA (Common Object Request Broker Architecture), in the prototype to enable multimedia data exchange and brain images transmission. The preliminary results show that the federated prototype system provides a uniform interface, heterogeneous information integration and efficient data sharing for users in our institution who are concerned with the care of patients with epilepsy and who pursue research in this area.

Animals↗