What is NeatVision
NeatVision data files are given the .dat suffix in the examples below. Netscape users can download .dat files by right clicking on the desired link and selecting 'Save Link As' from the resulting menu.
Each data connection has two properties
data type and connection status. There are currently 8 supported data types,
these are listed below.
The other connection property is it's status. There are two main states for a connection, connected and disconnected. There is also an addition sub state disconnected but using default value, these states and associated colours are listed below.
Aim:Edge Detection. A range of the edge detectors available to NeatVision are applied to a sample image. A user defined threshold (integer input) is applied prior to applying the binary border block. Alternatively, this can be chosen interactively using the blocks slide bar (activate by double clicking the threshold block).
dat File: edgedetector.dat
Aim: Isolate the largest item in the field of view. The input image is passed through a threshold block with a user defined level of 74 prior to erosion. The image is eroded to remove small white regions. The image is then labelled (i.e. a unique grey scale is applied to every distinct binary object). The processing flow path is split to allow multiple operations on the same data. The lower path allows the image to be enhanced and sent to an output window. The upper path data is passed through a dual threshold block, allowing a unique blob to be isolated and displayed. The input values to the dual threshold can be either predefined integer inputs, or the user can select them interactively via the slide bars.
dat File: largest.dat
dat File: feedback.dat
dat File: ifelse.dat
dat File: forloop.dat
data manipulation. This example illustrates how you can process data from
a DICOM sequence (*.dcm) and store the modified data as a DICOM sequence.
The original DICOM header is stripped from the original sequence and forms
the header for the new processed sequence. The top example illustrates
how we can take a single image from the volume, perform a Sobel edge detection
operation on it and replace the modified data in the DICOM sequence. The
bottom example illustrates how by employing looping we can doe this for
the full DICOM sequence.