IEICE Technical Report

Online edition: ISSN 2432-6380

Volume 124, Number 448

Medical Imaging

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Table of contents

MI2024-47
(See Japanese page.)
pp. 1 - 4

MI2024-48
(See Japanese page.)
pp. 5 - 8

MI2024-49
Construction of a Pseudo-3D U-Net Model with Attention Gates for Spinal Segmentation from CT Images
Kai Yang, Masayuki Kikuchi (Tokyo Univ. of Tech.)
pp. 9 - 12

MI2024-50
Anomaly Region Detection by Progressive Mask Refinement using Diffusion Models
Hiroki Tobise (NIT), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi (Juntendo Univ.), Hidekata Hontani (NIT)
pp. 13 - 16

MI2024-51
An Investigation of Labeled Data Ratio in Uncertainty-Aware Semi-Supervised Learning for Multi-Organ Segmentation
Guotai Dong, Masahiro Oda, Yuichiro Hayashi (Nagoya Univ.), Kazunari Misawa (Aichi Cancer Center), Kensaku Mori (Nagoya Univ.)
pp. 17 - 20

MI2024-52
[Invited Talk] Radiomics research to support genomic medicine
Yoshikazu Uchiyama (Univ. of Miyazaki)
pp. 21 - 23

MI2024-53
[Invited Lecture] Latest Research Trends 2024: Image Segmentation and General Overview of MICCAI
Masahiro Oda (Nagoya Univ.), Ryo Furukawa (Kindai Univ.), Kensaku Mori (Nagoya Univ.)
pp. 24 - 27

MI2024-54
[Invited Lecture] Latest Research Trends 2024: Image Registration
Yoshito Otake, Sato Yoshinobu (NAIST)
pp. 28 - 30

MI2024-55
[Invited Lecture] Latest Research Trends 2024: Multimodal Learning in Medical Imaging
Yi Gu, Ganping Li (NAIST)
pp. 31 - 33

MI2024-56
[Invited Lecture] Latest Research Trends 2024: Computer-Aided Therapy
Ken'ichi Morooka (Kumamoto Univ.), Tomoko Yamaguchi (Kobe Univ.)
pp. 34 - 36

MI2024-57
[Invited Lecture] Latest Research Trends 2024: Pathological Image Analysis
Shinnosuke Matsuo, Ryoma Bise (Kyushu Univ.)
pp. 37 - 40

MI2024-58
[Invited Lecture] Latest Research Trends 2024:Ophthalmic Image Processing
Koichi Ito, Tsubasa Konno (Tohoku Univ.)
pp. 41 - 47

MI2024-59
(See Japanese page.)
pp. 48 - 51

MI2024-60
[Poster Presentation] Study on Deep Learning Reconstruction of MR Images based on signal space partitioning
Hagiwara Taiki, Ouchi Shohei (NITOC)
pp. 52 - 55

MI2024-61
Performance evaluation of Image Reconstruction Models in Deep Learning-based MR Simultaneous Multi-slice Imaging
Haruki Takeichi, Masaki Furuta, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.)
pp. 56 - 59

MI2024-62
A study on MRI fast T1 mapping using MP2RAGE -- Comparison between signal intensity function and deep learning methods --
Riko Naito, Yuta Endo, Sanae Takahashi, Haruna Shibo, Takeyuki Hashimoto, Shigehide Kuhara (Kyorin Univ.)
pp. 60 - 63

MI2024-63
(See Japanese page.)
pp. 64 - 67

MI2024-64
Automatic Reconstruction of Panoramic X-ray Images Using CT Images
Ichi Hasegawa, Kento Morita (Mie Univ.), Junya Hirota, Daisuke Takeda, Takumi Hasegawa, Masaya Akashi (Kobe Univ.), Tetsushi Wakabayashi (Mie Univ.)
pp. 68 - 71

MI2024-65
Classification and Generation Model for Pathological Image Observation Videos
Shota Kawakami (Nagoya Univ.), Noriaki Hashimoto (RIKEN), Hiroaki Miyoshi (Kurume Univ.), Jun Sakuma (Science Tokyo), Hidekata Hontani (NITech), Koichi Ohshima (Kurume Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN)
pp. 72 - 75

MI2024-66
Two-step Prediction of MRONJ Lesion in Dental X-ray Radiograph Using Deep Learning
Manami Inoue, Kento Morita (Mie Univ.), Yasuaki Sadakane, Takumi Hasegawa, Masaya Akashi (Kobe Univ.), Tetsushi Wakabayashi (Mie Univ.)
pp. 76 - 79

MI2024-67
Dental data analysis
Kenichi Nomura (Osaka Univ.), Sim, David Jr (UCSB), Hideaki Hayashi, Ryota Takaoka, Hajime Nagahara, Masahiro NIshimura (Osaka Univ.)
pp. 80 - 83

MI2024-68
[Short Paper] Region-of-Interest Segmentation in DCE-MR images for TIC Analysis of Salivary Gland Tumors
Kei Saito, Keita Takeda, Misa Sumi, Tomoya Sakai (Nagasaki Univ.)
pp. 84 - 85

MI2024-69
(See Japanese page.)
pp. 86 - 87

MI2024-70
[Short Paper] Feature Learning of Ultrasound Images by Sorting loss for grades -- for diagnosis of Sjogren's syndrome --
Takumi Ishibashi, Tomoya Sakai, Keita Takeda, Takagi Yukinori, Misa Sumi (Nagasaki Univ.)
pp. 88 - 89

MI2024-71
(See Japanese page.)
pp. 90 - 93

MI2024-72
Quantitative Evaluation of Deep-Learning-based Motion Estimation for Colonoscopy
Natsu Onozaka (Nagoya Univ.), Hayato Itoh (Fukuoka Univ./Nagoya Univ.), Oda Masahiro (Nagoya Univ.), Masashi Misawa (Showa Univ.), Yuichi Mori (UiO./Showa Univ.), Shin-ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ./NII)
pp. 94 - 97

MI2024-73
Learning from Label Proportions for Cell Image Classification
Momoko Imakubo (Sysmex), Hideaki Hayashi, Hajime Nagahara (Osaka Univ)
pp. 98 - 101

MI2024-74
Automatic detection of contrast agent injection timing from coronary angiography images using labeling and camera motion correction
Yuki Daijou, Ryo Haraguchi (University of Hyogo), Yuta Motani
pp. 102 - 105

MI2024-75
[Short Paper] Construction of a Pathology Image Classifier with Quantifiable Uncertainty Evaluation for Cancer Diagnosis Assistance
Jiro Onoki, Yasuyuki Tsuchimoto, Tatsuya Yokota (NIT), Koichi Ohshima, Hiroaki Miyoshi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (RIKEN/Nagoya Univ.), Hidekata Hontani (NIT)
pp. 106 - 107

MI2024-76
Indocyanine Green Fluorescence Image Analysis for Prediction of Skin Flap Necrosis with Arterial Ischemia or Venous Congestion
Funo Suzuki, Momoka Takamiya, Shinsuke Akita, Mitsukawa Nobuyuki, Takayuki Okamoto, Hideaki Haneishi (Chiba Univ.)
pp. 108 - 110

MI2024-77
Do medical VLMs discover discriminative features in multi-modal medical images?
Keita Takeda, Yuta Matsumura, Akihiro Miyake, Tomoya Sakai (Nagasaki Univ.)
pp. 111 - 114

MI2024-78
(See Japanese page.)
pp. 115 - 118

MI2024-79
Reconstruction experiments of Acquired Slice Image Data in Deep Learning-based MR Simultaneous Multi-slice Imaging
Satoshi ITO, Naoya Endo, Kazuki Yamato (Utsunomiya Univ.)
pp. 119 - 121

MI2024-80
[Short Paper] Accelerated MRI Reconstruction by Using Diffusion Model
Shunsuke Fukutomi, Tatsuya Yokota, Hidekata Hontani (NITech)
pp. 122 - 123

MI2024-81
[Short Paper] Generation of Counterfactual Pathology Images for Observing Changes in Cell Tissues with Cancerization in Malignant Lymphoma
Ryoichi Koga, Tatsuya Yokota (NITech), Koichi Ohshima, Hiroaki Miyoshi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NITech)
pp. 124 - 125

MI2024-82
[Short Paper] Pial Surface based Electric field regression with Neural Networks for Transcranial Magnetic Stimulation
Toyohiro Maki, Tatsuya Yokota, Akimasa Hirata, Hontani Hidekata (Nitech)
pp. 126 - 127

Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.