Interpretation of Medical Imaging Data with a Mobile Application: A Mobile Digital Imaging Processing Environment

Abstract

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users’ expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

A high-throughput neurohistological pipeline for brain-wide mesoscale connectivity mapping of the common marmoset

“…( a ) A quality control site (snapshot on the bottom left) which helps improve the pipelines process speed and manually flags unnecessary sections to avoid further post-processing. ( b ) An Openlayer 3.0 JPEG2000 viewer (snapshot on the bottom middle) including several controls such as dynamic range, gamma, measurement and auto cell detection tool to allow for a users’ interpretation (Lin et al, 2013). ( c ) The data portal site (snapshots on the bottom right) helps to host all successful and processed dataset for publishing purposes.…”

BrainBrowser: distributed, web-based neurological data visualization

“…TissueStack 4 (Lin et al, 2013 ) is an open-source application for visualizing MINC and NIfTI (Cox et al, 2004 ) files on the web. It is composed of an image server that tiles the volume to be visualized, a configuration database and an HTML5-based client for rendering the tiles.…”

Development of MRI‐based atlases of non‐human brains

“…However, increases in the processing power of readily available or commodity computer hardware and the ability to disseminate atlases via the web using modern HTML5 and Adobe Flash–based web interfaces have minimized this issue. Examples of such websites include those of the Allen Institute of Brain Science, The Scalable Brain Atlas (Bakker et al, ), the online BigBrain data set at the Montreal Neurological Institute (Amunts et al, ), and other TissueStack‐based websites (Lin et al, ). The increased speed of institutional and domestic Internet connections has greatly benefited the dissemination and use of large MRI data sets.…”