Our Mission
- Vision : Support patients with early detection
- Mission : Support doctors’ consultations by providing service / hardware utilizing imaging technology
- Value : Improve accuracy & Efficiency of medical care
Volume attention.
What is D'z IMAGE?
Image-based diagnostics innovations through medical-engineering collaboration
Based on its R&D concept of "achieving reality through imaging technology," Casio has launched a medical technology collaboration based on years of experience in pioneering image processing technology that has produced innovations in image-based diagnostics.
Our goal is to make meaningful contributions to medicine and to society more broadly by developing solutions that will not only provide patients with more accurate and effective examinations, but also help physicians in clinical settings to work more effectively and make earlier diagnoses.
News from CASIO
・Press release
- September 27, 2018
Casio to Launch English Version of Online Dermoscopy Learning Services for Physicians
02/19/2020
Three Casio Products Win iF Design Award 2020
- October 22, 2020
Casio to Exhibit Medical Camera for Global Market at virtual.MEDICA 2020
- January 26, 2021
Casio to Release DERMOCAMERATM, Allowing Dermatologists to Capture Close-up and Ordinary Shots of Affected Areas Using a Single Device
03/29/2021
Casio Announces Acquisition of ISO 13485 Certification by Yamagata Casio
・Exhibition & Meeting
- 2022 AAD Annual Meeting
Our stand no.: 3754
AI Diagnosis Support
* ISBI: International Symposium on Biomedical Imaging (refer)
* ISIC: International Standard Industrial Classification of All Economic Activities
* AMED: Japan Agency for Medical Research and Development (refer)
ISBI’s Link https://biomedicalimaging.org/2017/challenges/
AMED’s Link https://www.amed.go.jp/en/
March 19, 2021：
2019:
“Skin cancer diagnostic solutions development using imaging data” research project, conducted jointly with Shinshu University, listed by the AMED as a “Project for Medical Device and Healthcare”.
2017:
Secured the highest score in the “ISBI Challenge 2017/Skin Lesion Analysis Towards Melanoma Detection/Part 3: Lesion Classification” organized by the ISIC.
2016:
Commence the technological development for an AI-based skin cancer diagnostic support system in collaboration with Shinshu University.