Compressus, Inc.

Bernadette Baclig

Albert Hernandez

Laszlo R Gasztonyi

Joel Rosenfield

Ronald G Gesell

Simon Liao

Raymundo Anaya

Gregory James Cooper

George P Mulopulos

Methods and systems for automating and managing efficient workflow for the viewing and analysis of diagnostic images within a healthcare enterprise network generate virtual worklists listing of healthcare data orders allocated to a specific destination. The methods and systems can provide flexible worklist viewing, system administration, and maximized diagnostic throughput.

Virtual worklist for analyzing medical images

A compression rate is selected for a data file representing an image wherein an image source and an image characterization is identified. Selection of a compression rate can be based upon the image source and the image characterization. The image source can be medical imaging device such as x-ray, CT scan, MRI, mammogram, sonogram, or other types of images. The image characterization can be an anatomical content of the image, a purpose of study of the image, or a diagnostic value of the source of the image.

Method and apparatus for adjustable image compression

Compressing a data file representing an image wherein one or more regions within the image are identified. At least one of the regions is selected and the data corresponding to the selected region is compressed at a different rate that the data corresponding to non-selected regions of the image. The different compression rates are selected to maintain a desired fidelity in an image reconstructed from the compressed data file. The different compression rates can be predetermined, selected by a user, or automatically selected. Compression rates can be based upon the type of image to be compressed such as x-ray, CT scan or MRI images, the structure that is being analyzed, parameters regarding the use of the image, system parameters such as storage capacity available, or bandwidth of a communication channel used to transmit the compressed file.

Method and apparatus for boundary-based image compression

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Fullerton, CA, United States of America

Bernadette Baclig