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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 93  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-03
09:05
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Generation of Counterfactual Pathology Images of Malignant Lymphoma using Diffusion Models
Ryoichi Koga, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-30
Malignant lymphoma has more than 70 subtypes. In the pathological diagnosis, a pathological image is observed to identif... [more] MI2023-30
pp.1-2
MI 2024-03-03
09:17
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Valid p-value for critical instances in multiple instance learning
Noriaki Hashimoto (RIKEN), Daiki Miwa (Nitech), Kosei Sumida (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi (Kurume Univ.), Jun Sakuma (Tokyo Tech/RIKEN), Hidekata Hontani (Nitech), Koichi Ohshima (Kurume Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2023-31
(To be available after the conference date) [more] MI2023-31
pp.3-6
MI 2024-03-03
16:42
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Using Label Uncertainty for Learning Cell Nuclei Type Classifier with Strongly Noisy Supervised Signals
Shingo Koide, Mauricio Kugler, Tatsuya Yokota (NIT), Koichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-57
In this study, we construct a type classifier for cell nuclei of malignant lymphomas. Labelling by type is not easy, eve... [more] MI2023-57
pp.79-80
MI 2024-03-04
11:10
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Identification of follicle segmentation and subtype in a lymph node HE-stained image based on the set of cell nuclei
Mizuki Moribe, Tatsuya Yokota (NIT), Koichi Oshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (NU), Hidekata Hontani (NIT) MI2023-72
In this paper, we report on a method for follicle segmentation and the identification of malignant lymphoma subtypes usi... [more] MI2023-72
pp.131-132
MI 2023-09-08
10:05
Osaka
(Primary: On-site, Secondary: Online)
[Short Paper] Construction of Cell Nucleus Classifier using Complementary-Label Learning towards the Quantification of Grading for Follicular Lymphoma
Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-14
In this paper, we report the cell type classification from a pathological image toward the subtype classification of mal... [more] MI2023-14
pp.1-2
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
13:30
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Selective Inference for a Combination of Feature Selection Algorithms
Tatsuya Matsukawa (Nagoya Univ.), Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Koichi Taji (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-1 IBISML2023-1
In data-driven science, classical statistical hypothesis testing does not provide an adequate reliability assessment bec... [more] NC2023-1 IBISML2023-1
pp.1-8
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
15:10
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Selective Inference for DNN-driven Saliency Map
Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Tomohiro Shiraishi (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-5 IBISML2023-5
The usefulness of image classification using DNN models has been confirmed in various fields, but the prediction mechani... [more] NC2023-5 IBISML2023-5
pp.30-34
MI 2023-03-06
17:56
Okinawa OKINAWA SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Short Paper] Generation of Counterfactual Images towards the Construction of Quantitatively Criteria in Malignant Lymphoma
Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (KU), Noriaki Hashimoto, Ichiro Takeuchi (NU), Hidekata Hontani (NIT) MI2022-100
In pathological diagnosis of malignant lymphoma, a H&E-staind pathological image is observed to identify the subtype. Ho... [more] MI2022-100
pp.123-124
PRMU, IBISML, IPSJ-CVIM [detail] 2023-03-03
16:25
Hokkaido Future University Hakodate
(Primary: On-site, Secondary: Online)
Fast Identification of Possible Model Parameter Update for Low-Rank Update of Training Data
Hiroyuki Hanada, Noriaki Hashimoto (RIKEN), Kouichi Taji, Ichiro Takeuchi (Nagoya Univ.) PRMU2022-123 IBISML2022-130
Machine learning methods often require re-training the training dataset with low-rank modifications (small number of ins... [more] PRMU2022-123 IBISML2022-130
pp.347-354
IBISML 2022-12-23
13:40
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
Multi-objective Bayesian Optimization for Identifying Distributionally-robust Pareto-frontier
Yu Inatsu (Nitech), Ichiro Takeuchi (Nagoya Univ./RIKEN) IBISML2022-59
Pareto optimization is one of the multi-objective optimization problems for multiple black-box functions. Recently, an o... [more] IBISML2022-59
pp.112-119
IBISML 2022-12-23
14:30
Kyoto Kyoto University
(Primary: On-site, Secondary: Online)
Selective Inference for Cluster Level Inference in Brain Image Analysis
Masaya Ikuta, Mizuki Sato (NITech), Akifumi Yamada (Nagoya Univ.), Vo Nguyen Le Duy (NITech/RIKEN), Ryo Emoto (Nagoya Univ.), Yuko Ishimaru, Yuka Takao, Atsushi Kawaguchi (Saga Univ.), Shigeyuki Matsui (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) IBISML2022-61
Cluster-level inference in brain image analysis is often employed to identify disease-related regions in brain disorders... [more] IBISML2022-61
pp.128-133
IBISML 2022-09-15
15:05
Kanagawa Keio Univ. (Yagami Campus)
(Primary: On-site, Secondary: Online)
Improving Efficiency of Regularization Path Computation in Safe Pattern Pruning via Multiple Referential Solutions
Takumi Yoshida (Nitech), Hiroyuki Hanada (RIKEN), Kazuya Nakagawa, Shinya Suzumura, Onur Boyar, Kazuki Iwata (Nitech), Shun Shimura, Yuji Tanaka (NaogyaU), Masayuki Karasuyama (Nitech), Kouichi Taji (NaogyaU), Koji Tsuda (UTokyo/RIKEN), Ichiro Takeuchi (NaogyaU/RIKEN) IBISML2022-38
Safe Screening and Safe Pattern Pruning are methods for efficiently modeling high-dimensional features by $L_1$-regulari... [more] IBISML2022-38
pp.39-46
MI 2022-07-08
14:00
Hokkaido
(Primary: On-site, Secondary: Online)
Cell type-specific tumor degree estimation in malignant lymphoma pathology images
Hiroki Masuda (NITech), Noriaki Hashimoto (RIKEN), Yusuke Takagi (NITech), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi, Kensaku Sato, Koichi Oshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2022-32
In the pathological diagnosis flow of malignant lymphoma, a type of blood cancer, it is important to identify the type o... [more] MI2022-32
pp.1-6
MI 2022-01-27
13:54
Online Online [Short Paper] Case-based Similar Image Retrieval for Pathological Images of Malignant Lymphoma Using Deep Metric Learning
Noriaki Hashimoto (RIKEN), Yusuke Takagi, Hiroki Masuda (NITech), Hiroaki Miyoshi, Kei Kohno, Miharu Nagaishi, Kensaku Sato, Koichi Ohshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (NITech/RIKEN) MI2021-78
We propose a novel method of case-based similar image retrieval for histopathological images of malignant lymphoma. We e... [more] MI2021-78
pp.144-145
IBISML 2022-01-18
09:05
Online Online [Tutorial Lecture] Introduction to Selective Inference
Ichiro Takeuchi (Nitech/RIKEN)
 [more]
IBISML 2022-01-18
13:40
Online Online More Powerful Selective Inference for K-means clustering with Application to Single Cell Analysis
Mizuki Sato, Yumehiro Omori, Yu Inatsu, Ichiro Takeuchi (NITech) IBISML2021-25
K-means clustering is the most famous clustering method because of its simplicity, and it has been applied to a wide ran... [more] IBISML2021-25
pp.54-60
PRMU 2021-12-16
10:45
Online Online Selective Inference for Multi-dimensional Multiple Change-Points
Ryota Sugiyama, Hiroki Toda (NIT), Vo Nguyen Le Duy (NIT/RIKEN), Yu Inatsu (NIT), Ichiro Takeuchi (NIT/RIKEN) PRMU2021-28
Detecting changes in the average structure of multi-dimensional sequence is an important task in various fields. Since c... [more] PRMU2021-28
pp.25-30
MI 2021-07-09
11:00
Online Online [Short Paper] Construction of Subtype Classifier for Malignant Lymphoma based on H&E-stained Images using Immuno-stainning Data
Yuki Hirono (NIT), Noriaki Hashimoto (RIKEN), Kugler Mauricio, Tatsuya Yokota (NIT), Miharu Nagaishi (Kurume Univ.), Hiroaki Miyoshi, Koichi Oshima (Kurume Univ./JSP), Ichiro Takeuchi (NIT/RIKEN), Hidekata Hontani (NIT) MI2021-16
In pathological diagnosis of malignant lymphoma, a HE image is observed at first and then a set of immunostained images ... [more] MI2021-16
pp.31-32
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
15:45
Online Online Active learning for distributionally robust chance-constrained optimization
Yu Inatsu, Shion Takeno, Masayuki Karasuyama (Nitech), Ichiro Takeuchi (Nitech/RIKEN) NC2021-7 IBISML2021-7
Chance-constrained optimization (CCO) is one of the constrained optimization problems where some of the inputs to a blac... [more] NC2021-7 IBISML2021-7
pp.47-54
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
16:10
Online Online More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
Kazuya Sugiyama (Nitech), Vo Nguyen Le Duy, Ichiro Takeuchi (Nitech/RIKEN) NC2021-8 IBISML2021-8
Conditional selective inference (SI) has been actively studied as a new statistical inference framework for data-driven ... [more] NC2021-8 IBISML2021-8
pp.55-61
 Results 1 - 20 of 93  /  [Next]  
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