Literature DB >> 10471238

High quality image oriented telemedicine with multimedia technology.

H Takeda1, K Minato, T Takahasi.   

Abstract

Researchers at Osaka and Kyoto University hospital performed three experiments, beginning in 1995, which looked at high quality-oriented telemedicine. This paper describes the system design for the three projects. Experiment 1 applied high-definition TV images and B-ISDN for distance learning and medical information exchange. Experiment 2 developed a super high-definition medical image filing system and the images were transmitted via B-ISDN for teleconferences and experiment 3 utilized digital, high-definition, TV images and communication satellites for teleconferences. Multimedia and communication technologies were considered to be fundamental components of telemedicine. The three projects were evaluated initially for quality of images, operability and utility. The experimental design and its implementation showed that it was possible to provide high quality image-oriented telemedicine in the health care environment. Obstacles to establishing practical telemedicine are also discussed.

Mesh:

Year:  1999        PMID: 10471238     DOI: 10.1016/s1386-5056(99)00017-9

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  4 in total

Review 1.  Theory and applications of telemedicine.

Authors:  Nihal Fatma Güler; Elif Derya Ubeyli
Journal:  J Med Syst       Date:  2002-06       Impact factor: 4.460

2.  A method to convert HDTV videos of broadcast satellite to RealSystem multimedia contents.

Authors:  Tomoko Yamakawa; Masao Hashiba; Tsukasa Koyama; Kouhei Akazawa
Journal:  J Med Syst       Date:  2002-10       Impact factor: 4.460

3.  Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

Authors:  Aaron S Coyner; Ryan Swan; James M Brown; Jayashree Kalpathy-Cramer; Sang Jin Kim; J Peter Campbell; Karyn E Jonas; Susan Ostmo; R V Paul Chan; Michael F Chiang
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

4.  Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

Authors:  Aaron S Coyner; Ryan Swan; J Peter Campbell; Susan Ostmo; James M Brown; Jayashree Kalpathy-Cramer; Sang Jin Kim; Karyn E Jonas; R V Paul Chan; Michael F Chiang
Journal:  Ophthalmol Retina       Date:  2019-01-31
  4 in total

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