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Technical Committee on Healthcare and Medical Information Communication Technology (MICT) (Searched in: 2023)
Search Results: Keywords 'from:2023-11-14 to:2023-11-14'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI, MICT | 2023-11-14 09:30 |
Fukuoka | Facial Symmetry Analysis Based on Extraction of Lip Region from 4D Data Narumi Kihara (KIT), Namiko Kimura-Nomoto, Takako Okawachi (Kagoshima Univ.), Guangxu Li (Tiangong Univ.), Norifumi Nakamura (Kagoshima Univ.), Tohru Kamiya (KIT)  MICT2023-25 MI2023-18 |
We propose an image processing method using 4D data (3D point cloud containing temporal changes) to quantitatively evalu... [more] | MICT2023-25 MI2023-18 pp.1-4 |
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| MI, MICT | 2023-11-14 10:30 |
Fukuoka | A Large-Scale Video Dataset of the Eyelid Opening Degree for Deep Regression-based PERCLOS Estimation Ko Taniguchi, Takahiro Noguchi, Satoshi Iizuka, Hiroyasu Ando, Takashi Abe, Kazuhiro Fukui (Univ. of Tsukuba) MICT2023-26 MI2023-19 |
In this study, we focus on the PERcent time of slow eyelid CLOSures (PERCLOS), an vigilance assessment index based on th... [more] | MICT2023-26 MI2023-19 pp.5-8 |
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| MI, MICT | 2023-11-14 10:50 |
Fukuoka | A Study on How to Classify Paralytic Strabismus Based on Ocular Motility Photographs Takeshi Noda, Koh Kakusho, Takeshi Okadome (Kwansei Gakuin Univ.), Yoichi Okita, Akiko Kimura, Fumi Gomi (Hyogo Medical Univ.) MICT2023-27 MI2023-20 |
In this paper, we discuss how to obtain the types of paralytic strabismus from ocular motility photographs of the patien... [more] | MICT2023-27 MI2023-20 pp.9-12 |
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| MI, MICT | 2023-11-14 11:10 |
Fukuoka | [Short Paper]
Choroid layer extraction for 3D OCT images using a deep learning network fusing CNN and Transformer Shingo Tamachi, Takayuki Okamoto, Takehito Iwase, Yuto Kawamata, Hirotaka Yokouchi, Hideaki Haneishi (Chiba Univ.) MICT2023-28 MI2023-21 |
The choroid, a dense vascular layer located in the fundus, accounts for the majority of the blood supply to the retina. ... [more] | MICT2023-28 MI2023-21 pp.13-14 |
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| MI, MICT | 2023-11-14 13:00 |
Fukuoka | Brain Disease Classification Based on Brain MRI Images Using 3D-CNN Daisuke Hayashi, Akio Nagasaka, Yuji Mochizuki, Takayuki Hayashi (Hitachi), Takefumi Ueno (NHO Hizen Psychiatric Center) MICT2023-29 MI2023-22 |
Schizophrenia and Alzheimer’s disease are brain diseases that cause structural changes in the brain. In this paper, we c... [more] | MICT2023-29 MI2023-22 pp.15-20 |
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| MI, MICT | 2023-11-14 13:20 |
Fukuoka | Medical image diagnosis support system with image anonymization based on deep learning techniques Katsuto Iwai, Ryuunosuke Kounosu (Toho Univ./AIST), Hirokazu Nosato (AIST), Yuu Nakajima (Toho Univ.) MICT2023-30 MI2023-23 |
When medical imaging AI models are hosted on cloud service there is a risk of sensitive medical images being leaked when... [more] | MICT2023-30 MI2023-23 pp.21-24 |
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| MI, MICT | 2023-11-14 13:40 |
Fukuoka | Arrhythmia Classification From Electrocardiogram by Gradient Boosting and Physician's Diagnosis-based algorithm. Haruto Shirae, Nobuhiro Nishii, Hiroshi Morita (Okayama Univ.), Ken'ichi Morooka (Kumamoto Univ.) MICT2023-31 MI2023-24 |
Implantable cardiac electrical devices can record a variety of arrhythmic events, but the determination of supraventricu... [more] | MICT2023-31 MI2023-24 pp.25-28 |
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| MI, MICT | 2023-11-14 14:00 |
Fukuoka | Estimating the degree of coronary artery stenosis from non-contrast CT images using a 3D convolution model
-- Categorical approach -- Hiroki Shinoda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuya Togawa, Kei Nomura (Toyohashi Heart Center), Masaki Aono (TUT) MICT2023-32 MI2023-25 |
In current medical images diagnosis, specialists take pictures of patients and search for the disease from the images. I... [more] | MICT2023-32 MI2023-25 pp.29-32 |
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| MI, MICT | 2023-11-14 14:40 |
Fukuoka | Construction of organ shape atlas by MeshVAE using hierarchical latent variables Ryuichi Umehara, Mitsuhiro Nakamura, Megumi Nakao (Kyoto University) MICT2023-33 MI2023-26 |
[more] | MICT2023-33 MI2023-26 pp.33-36 |
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| MI, MICT | 2023-11-14 15:00 |
Fukuoka | Pre-training without natural images for Cystoscopic AI Diagnosis of Bladder Cancer Ryuunosuke Kounosu (AIST/Toho Univ.), Wonjik Kim (AIST), Atsushi Ikeda (Univ. of Tsukuba), Hirokazu Nosato (AIST), Yuu Nakajima (Toho Univ.) MICT2023-34 MI2023-27 |
When developing AI models, it is sometimes difficult to collect sufficient training data. In these cases, pre-trained AI... [more] | MICT2023-34 MI2023-27 pp.37-40 |
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| MI, MICT | 2023-11-14 15:20 |
Fukuoka | Generation of pseudo-CT images from phalanges CR images based on deep learning
-- Accuracy comparison using pix2pix and CycleGAN -- Rensuke Ueno, Takaharu Yamazaki (SIT), Kazuaki Tanaka (Neomedical Corporation), Keizo Fukumoto (Saitama Jikei Hospital) MICT2023-35 MI2023-28 |
In this study, we perform generation to pseudo-CT images from phalanges CR images using deep learning. For the image gen... [more] | MICT2023-35 MI2023-28 pp.41-44 |
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| MI, MICT | 2023-11-14 15:40 |
Fukuoka | Improving image quality of sparse-view micro-CT using Wasserstein GAN Naoki Ikezawa, Takayuki Okamoto, Hideaki Haneishi (Chiba Univ.) MICT2023-36 MI2023-29 |
Applications of micro-CT in pathology and histology have been studied in recent years, and we need to shorten the scanni... [more] | MICT2023-36 MI2023-29 pp.45-47 |
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