Literature DB >> 10566395

Multiresolution browsing of pathology images using wavelets.

J Z Wang1, J Nguyen, K K Lo, C Law, D Regula.   

Abstract

Digitized pathology images typically have very high resolution, making it difficult to display in their entirety on the computer screen and inefficient to transmit over the network for educational purposes. Progressive zooming of pathology images is desirable despite the availability of inexpensive networking bandwidth. An efficient progressive image resolution refining system for on-line distribution of pathology image using wavelets has been developed and is discussed in this paper. The system is practical for real-world applications, pre-processing and coding each 24-bit image of size 2400 x 3600 within 40 seconds on a Pentium II PC. The transmission process is in real-time. Besides its exceptional speed, the algorithm has high flexibility. The server encodes the original pathology images without loss. Based on the image request from a client, the server dynamically generates and sends out the part of the image at the requested scale and quality requirement. The algorithm is expandable for medical image databases such as PACS.

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Year:  1999        PMID: 10566395      PMCID: PMC2232834     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  3 in total

1.  ImageMiner: a software system for comparative analysis of tissue microarrays using content-based image retrieval, high-performance computing, and grid technology.

Authors:  David J Foran; Lin Yang; Wenjin Chen; Jun Hu; Lauri A Goodell; Michael Reiss; Fusheng Wang; Tahsin Kurc; Tony Pan; Ashish Sharma; Joel H Saltz
Journal:  J Am Med Inform Assoc       Date:  2011-05-23       Impact factor: 4.497

2.  A data model and database for high-resolution pathology analytical image informatics.

Authors:  Fusheng Wang; Jun Kong; Lee Cooper; Tony Pan; Tahsin Kurc; Wenjin Chen; Ashish Sharma; Cristobal Niedermayr; Tae W Oh; Daniel Brat; Alton B Farris; David J Foran; Joel Saltz
Journal:  J Pathol Inform       Date:  2011-07-26

3.  Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Authors:  Hyeongsub Kim; Hongjoon Yoon; Nishant Thakur; Gyoyeon Hwang; Eun Jung Lee; Chulhong Kim; Yosep Chong
Journal:  Sci Rep       Date:  2021-11-18       Impact factor: 4.379

  3 in total

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