Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet

碩士 === 國立臺灣科技大學 === 醫學工程研究所 === 101 === Histopathology is the study of the microscopic anatomy of cells and tissues using microscopy techniques or electron microscope. During the past many decades, the pathologist sliced the cells or tissue into very thin layers that are mounted on a glass slide and...

Full description

Bibliographic Details
Main Authors: Chu-mei Hung, 洪楚媚
Other Authors: Ching-Wei Wang
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/50454858547182195274
id ndltd-TW-101NTUS5159009
record_format oai_dc
spelling ndltd-TW-101NTUS51590092016-03-21T04:28:01Z http://ndltd.ncl.edu.tw/handle/50454858547182195274 Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet 超高速巨量超高解析醫學影像雲端互動顯示技術 Chu-mei Hung 洪楚媚 碩士 國立臺灣科技大學 醫學工程研究所 101 Histopathology is the study of the microscopic anatomy of cells and tissues using microscopy techniques or electron microscope. During the past many decades, the pathologist sliced the cells or tissue into very thin layers that are mounted on a glass slide and examined under a microscope. With the recent advent of digital imaging, high-resolution digital images are necessary for accurate diagnosis, and it is expected to play a revolutionary role in future histopathology. In the past, biomedical image database can be only stored string data such as DNA sequences and low-resolution images. Most existing large-scale image techniques have bandwidth and storage limitations, so images must be lossy compressed to solve this problems before transmission and storage [1]. It is difficult to display high resolution microscopic images over internet in real time. This thesis presents two ultra fast super high resolution image cloud systems, which enables users to interactively view large, high resolution images within existing web browsers in real time. In evaluation, the method1 is demonstrated to render large high resolution image over internet in real time (0.5~0.67 second on average), and the results show that the method1 performs 3~4 times faster than method2 in rendering large high resolution images while costs approximately half of storage space method1 requires. However, the encoding time of method2 are 1.4 times faster than method1 due to following reasons, the regular encoding of the method2, and the complicated structure of the method1, but it is unnecessary to encode image dimension to 1*1 of the method2. Ching-Wei Wang 王靖維 2013 學位論文 ; thesis 76 en_US
collection NDLTD
language en_US
format Others
sources NDLTD
description 碩士 === 國立臺灣科技大學 === 醫學工程研究所 === 101 === Histopathology is the study of the microscopic anatomy of cells and tissues using microscopy techniques or electron microscope. During the past many decades, the pathologist sliced the cells or tissue into very thin layers that are mounted on a glass slide and examined under a microscope. With the recent advent of digital imaging, high-resolution digital images are necessary for accurate diagnosis, and it is expected to play a revolutionary role in future histopathology. In the past, biomedical image database can be only stored string data such as DNA sequences and low-resolution images. Most existing large-scale image techniques have bandwidth and storage limitations, so images must be lossy compressed to solve this problems before transmission and storage [1]. It is difficult to display high resolution microscopic images over internet in real time. This thesis presents two ultra fast super high resolution image cloud systems, which enables users to interactively view large, high resolution images within existing web browsers in real time. In evaluation, the method1 is demonstrated to render large high resolution image over internet in real time (0.5~0.67 second on average), and the results show that the method1 performs 3~4 times faster than method2 in rendering large high resolution images while costs approximately half of storage space method1 requires. However, the encoding time of method2 are 1.4 times faster than method1 due to following reasons, the regular encoding of the method2, and the complicated structure of the method1, but it is unnecessary to encode image dimension to 1*1 of the method2.
author2 Ching-Wei Wang
author_facet Ching-Wei Wang
Chu-mei Hung
洪楚媚
author Chu-mei Hung
洪楚媚
spellingShingle Chu-mei Hung
洪楚媚
Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
author_sort Chu-mei Hung
title Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
title_short Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
title_full Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
title_fullStr Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
title_full_unstemmed Ultra Fast Super High Resolution Medical Image Interactive Visualization Technique Over Internet
title_sort ultra fast super high resolution medical image interactive visualization technique over internet
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/50454858547182195274
work_keys_str_mv AT chumeihung ultrafastsuperhighresolutionmedicalimageinteractivevisualizationtechniqueoverinternet
AT hóngchǔmèi ultrafastsuperhighresolutionmedicalimageinteractivevisualizationtechniqueoverinternet
AT chumeihung chāogāosùjùliàngchāogāojiěxīyīxuéyǐngxiàngyúnduānhùdòngxiǎnshìjìshù
AT hóngchǔmèi chāogāosùjùliàngchāogāojiěxīyīxuéyǐngxiàngyúnduānhùdòngxiǎnshìjìshù
_version_ 1718209505335967744