Project

A Study on Medical Virtual Reality, Medical Imaging, and Diagnostic Imaging System

Goal: To apply virtual reality technology (including AR, MR) for medical imaging systems.

Date: 1 April 2017

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Project log

Norifumi Kawabata
added a research item
As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical image processing, there are many studies improved performance and precision of processing by contrast enhancement or super-resolution. However, it is not clarified how condition is better to apply these methods. Therefore, we experimented and discussed on affect for color laparoscopic image quality by the difference of contrast enhancement method. As a result, we obtained knowledge of high similarity among patterns of adaptive histogram equalization in three methods. However, under these conditions, in the case of considering the region segmentation, it is not clarified how processing precision is better. In this paper, first we processed the contrast enhancement for the color laparoscopic frame image cut from surgery video under laparoscopy. Next, we processed super-resolution for generated image. Finally, we compared and discussed by Peak Signal to Noise Ratio (PSNR), Structural SIMilarity (SSIM), and texture features for contrast.
Norifumi Kawabata
added a research item
In medical images, since there are body region and border that it is hard for medical worker to distinguish by the only image diagnosis, we estimate that the progress of work, time, and emergency are needed. Therefore, it is problem of emergency to develop the medical information system enable to support medical workers by using high performance computer. In this study, first, we carried out texture analysis for region of laparoscopic image. Next, based on results, we experimented whether region segmentation of laparoscopic image is possible or impossible. Finally, we discussed how each texture features are affected to region segmentation.
Norifumi Kawabata
added an update
1 paper has been accepted and presented as Short Presentation and Poster in the 5th Asia Color Association Conference (ACA2019 Nagoya) held at Meijo University, Nagoya, Japan.
 
Norifumi Kawabata
added 2 research items
In this paper, first, we generated medical images cut as frame still image from laparoscopic video acquired by endoscopy. Using these images, we processed to encode and decode by H.265/HEVC in certain image regions, and we generated evaluation images. Next, we evaluated objectively seeing from the coded image quality by using PSNR (Peak Signal to Noise Ratio), considering the automatic detection of coded defect region information. Furthermore, we analyzed for color information by measuring both the luminance using S-CIELAB color space and the color difference using CIEDE2000. Finally, we try to classify effectively using Support Vector Machine (SVM), and we discussed including the automatic detection of coded defect region information whether it is possible for application of medical image diagnosis or not.
Norifumi Kawabata
added an update
We participated and presented in JAMIT2019 (in Japanese) held at Nara kasugano International Forum --IRAKA-- on July 24-26, 2019.
 
Norifumi Kawabata
added an update
We participated and presented in ITE Media Engineering Technical Meeting (in Japanese) held at Hokkaido University on February 19, 20, 2019.
 
Norifumi Kawabata
added an update
We participated and presented in IEICE Medical Imaging Technical Meeting (in Japanese) held at Kobe Campus for Information Science, University of Hyogo on November 6, 2018.
 
Norifumi Kawabata
added a research item
Up to now, the diagnostic imaging was carried out based on manual handling by professional doctors and health care workers. However, it is enable to diagnose images automatically by development of the computer systems. Therefore, it is required for approach from information science and engineering fields. For generating multi-view 3D images, if we are able to support whether workers are able to use correctly or not, and if the coded defect detection and restoration for their images are possible, we consider possibility towards medical applications in the near future. In this paper, first, we diagnosed automatically for multi-view 3D images in the case of occurring defect by encoded and decoded degradation at all or certain viewpoints by H.265/HEVC. Next, we assessed and estimated quantitatively in terms of the coded image quality in order to clarify how we are able to detect the coded defect.
Norifumi Kawabata
added an update
One international conference paper has been accepted to the Ninth International Workshop on Image Media Quality and its Applications (IMQA2018).
Norifumi Kawabata, “Image Diagnosis for Coded Defect Detection on Multi-view 3D Images," Proc. of The Ninth International Workshop on Image Media Quality and its Applications (IMQA2018), 10 pages, Kobe Univ., September 27-28, 2018 (Accepted).
 
Norifumi Kawabata
added a research item
Up to now, the diagnostic imaging was carried out based on manual handling by professional doctors and health care workers. However, it is enable to diagnose images automatically by development of the computer systems. Therefore, it is required for approach from information science and engineering fields. For generating multi-view 3D images, if we are able to support whether workers are able to use correctly or not, and if the coded defect detection and restoration for their images are possible, we consider possibility towards medical applications in the near future. In this paper, first, we diagnosed automatically for multi-view 3D images in the case of occurring defect by encoded and decoded degradation at all or certain viewpoints by H.265/HEVC. Next, we assessed and estimated quantitatively in terms of the coded image quality in order to clarify how we are able to detect the coded defect.
Norifumi Kawabata
added an update
At present, we are preparing for presentation in Japanese Society of Medical Imaging Technology Annual Meeting (JAMIT2018) held at University of Tsukuba on July 25-27.
 
Norifumi Kawabata
added an update
Norifumi Kawabata has been finished participation and presentation in front of participants in the image engineering technical meeting held at Hokkaido Univ (so called Hokudai) on February 15, 2018 (in Japanese).
 
Norifumi Kawabata
added an update
Norifumi Kawabata will participate and present in front of participants in the image engineering technical meeting held at Hokkaido Univ (so called Hokudai) on February 15, 2018 (in Japanese).
 
Norifumi Kawabata
added an update
I have finished participation and presentation in IMQ technical meeting on December 15 held at Hamamatsu Campus, Shizuoka University by using Power Point in front of participants.
Norifumi Kawabata, “A Study of Diagnostic Imaging System for Coded Defect Detection of Certain Viewpoints on Multi-view 3D CG Images," IEICE Tech. Rep., Image Media Quality, vol. 117, no. 356, IMQ2017-21, pp. 7--12, Shizuoka Univ., December 2017 (in Japanese).
 
Norifumi Kawabata
added an update
I have finished participation and presentation (in the Poster Session, November 21, 2017) in The 32nd Picture Coding Symposium of Japan / The 22nd Image Media Processing Symposium (PCSJ/IMPS2017) on November 20-22, 2017 held at Laforet Shuzenji.
Norifumi Kawabata, “A Study of Diagnostic Imaging System for Coded Defect Detection on Multi-view 3D CG Images", Proc. of Picture Coding Symposium of Japan / Image Media Processing Symposium (PCSJ/IMPS2017), P-4-01, pp.130--131, Laforet Shuzenji, November 2017 (in Japanese).
 
Norifumi Kawabata
added a project goal
To apply virtual reality technology (including AR, MR) for medical imaging systems.