Search Results - "Nosato, Hirokazu"

The Digital Transformation(Dx)of Endoscopic Examinations by Ikeda, Atsushi, Nosato, Hirokazu

“…Artificial intelligence(AI)and information and communication technology(ICT)are beginning to be used in the digital transformation of endoscopic images. In…”
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CTG-Net: Cross-task guided network for breast ultrasound diagnosis by Yang, Kaiwen, Suzuki, Aiga, Ye, Jiaxing, Nosato, Hirokazu, Izumori, Ayumi, Sakanashi, Hidenori

“…Deep learning techniques have achieved remarkable success in lesion segmentation and classification between benign and malignant tumors in breast ultrasound…”
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Integration of human inspection and artificial intelligence‐based morphological typing of patient‐derived organoids reveals interpatient heterogeneity of colorectal cancer by Okamoto, Takuya, Natsume, Yasuko, Doi, Motomichi, Nosato, Hirokazu, Iwaki, Toshiyuki, Yamanaka, Hitomi, Yamamoto, Mayuko, Kawachi, Hiroshi, Noda, Tetsuo, Nagayama, Satoshi, Sakanashi, Hidenori, Yao, Ryoji

“…Colorectal cancer (CRC) is a heterogenous disease, and patients have differences in therapeutic response. However, the mechanisms underlying interpatient…”
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Development of a motion-based cell-counting system for Trypanosoma parasite using a pattern recognition approach by Takagi, Yuko, Nosato, Hirokazu, Doi, Motomichi, Furukawa, Koji, Sakanashi, Hidenori

“…Automated cell counters that utilize still images of sample cells are widely used. However, they are not well suited to counting slender, aggregate-prone…”
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Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks by Murakawa, Masahiro, Nosato, Hirokazu, Terai, Kensuke, Hiruta, Nobuyuki, Qu, Jia, Sakanashi, Hidenori

“…Deep learning using convolutional neural networks (CNNs) is a distinguished tool for many image classification tasks. Due to its outstanding robustness and…”
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Deep Learning Models for Cystoscopic Recognition of Hunner Lesion in Interstitial Cystitis by Iwaki, Takuya, Akiyama, Yoshiyuki, Nosato, Hirokazu, Kinjo, Manami, Niimi, Aya, Taguchi, Satoru, Yamada, Yuta, Sato, Yusuke, Kawai, Taketo, Yamada, Daisuke, Sakanashi, Hidenori, Kume, Haruki, Homma, Yukio, Fukuhara, Hiroshi

“…In this diagnostic study, we developed the first deep learning system for cystoscopic recognition of a Hunner lesion in patients with interstitial cystitis,…”
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Diagnosis and Localization of Prostate Cancer via Automated Multiparametric MRI Equipped with Artificial Intelligence by Oishi, Yuichiro, Kitta, Takeya, Osawa, Takahiro, Abe, Takashige, Shinohara, Nobuo, Nosato, Hirokazu, Sakanashi, Hidenori, Murakawa, Masahiro

“…Prostate MRI scans for pre-biopsied patients are important. However, fewer radiologists are available for MRI diagnoses, which requires multi-sequential…”
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DEVELOPING AN EXPLAINABLE AI MODEL FOR DIAGNOSIS AND PROGNOSIS IN INTERSTITIAL LUNG DISEASE by Uegami, Wataru, Uehara, Kazuki, Bychkov, Andrey, Ozasa, Mutsumi, Okoshi, Ethan N., Johkoh, Takeshi, Kataoka, Kensuke, Kondoh, Yasuhiro, Nosato, Hirokazu, Sakanashi, Hidenori, Bychkov, Andrey, Fukuoka, Junya

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Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images by Suzuki, Yasuo, Aoki, Hiroshi, Murakawa, Masahiro, Takahashi, Eiichi, Sakanashi, Hidenori, Nosato, Hirokazu, Takeuchi, Ken

“…Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy…”
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Overview of current applications and trends in artificial intelligence for cystoscopy and transurethral resection of bladder tumours by Ikeda, Atsushi, Nosato, Hirokazu

“…Purpose of review Accurate preoperative and intraoperative identification and complete resection of bladder cancer is essential. Adequate postoperative…”
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MP07-12 DEVELOPING A DEEP LEARNING METHOD FOR DETECTING FALSE POSITIVES IN PHOTODYNAMIC DIAGNOSIS by Yamamoto, Shinkuro, Nosato, Hirokazu, Ikeda, Atsushi, Fukuhara, Hideo, Inoue, Keiji

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PD27-08 PRE-TRAINING AN AI MODEL USING TWO TYPES OF AUTOMATICALLY GENERATED IMAGES FOR CYSTOSCOPY AI DIAGNOSIS OF BLADDER CANCER by Ikeda, Atsushi, Kounosu, Ryuunosuke, Kim, Wonjik, Nosato, Hirokazu, Nakajima, Yuu, Nishiyama, Hiroyuki

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PD13-03 A CYSTOSCOPY ARTIFICIAL INTELLIGENCE SYSTEM THAT CAN BE USED WITH CYSTOSCOPES PRODUCED BY DIFFERENT MANUFACTURERS by Ikeda, Atsushi, Nosato, Hirokazu, Takaoka, Shogo, Negoro, Hiromitsu, Sakanashi, Hidenori, Murakawa, Masahiro, Nishiyama, Hiroyuki

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Support System of Cystoscopic Diagnosis for Bladder Cancer Based on Artificial Intelligence by Ikeda, Atsushi, Nosato, Hirokazu, Kochi, Yuta, Kojima, Takahiro, Kawai, Koji, Sakanashi, Hidenori, Murakawa, Masahiro, Nishiyama, Hiroyuki

“…Nonmuscle-invasive bladder cancer has a relatively high postoperative recurrence rate despite the implementation of conventional treatment methods. Cystoscopy…”
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PD26-02 REAL-TIME BLADDER TUMOR DETECTION AT CLINICS IN FLEXIBLE CYSTOSCOPY WITH WHITE LIGHT AND NARROW BAND IMAGING USING DEEP LEARNING by Ikeda, Atsushi, Takaoka, Shogo, Nosato, Hirokazu, Negoro, Hiromitsu, Sakanashi, Hidenori, Murakawa, Masahiro, Nishiyama, Hiroyuki

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Object detection of satellite images using multi-channel higher-order local autocorrelation by Uehara, Kazuki, Sakanashi, Hidenori, Nosato, Hirokazu, Murakawa, Masahiro, Miyamoto, Hiroki, Nakamura, Ryosuke

“…The Earth observation satellites have been monitoring the earth's surface for a long time, and the images taken by the satellites contain large amounts of…”
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Development of a motion-based cell-counting system for by Takagi, Yuko, Nosato, Hirokazu, Doi, Motomichi, Furukawa, Koji, Sakanashi, Hidenori

“…Automated cell counters that utilize still images of sample cells are widely used. However, they are not well suited to counting slender, aggregate-prone…”
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PD03-04 SUPPORT SYSTEM OF CYSTOSCOPIC DIAGNOSIS FOR BLADDER CANCER BASED ON ARTIFICIAL INTELLIGENCE SURPASSES UROLOGISTS by Ikeda, Atsushi, Kochi, Yuta, Nosato, Hirokazu, Kojima, Takahiro, Sakanashi, Hidenori, Murakawa, Masahiro, Nishiyama, Hiroyuki

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Multi-channel higher-order local autocorrelation for object detection on satellite images by Uehara, Kazuki, Nosato, Hirokazu, Murakawa, Masahiro, Nakamura, Ryosuke, Miyamoto, Hiroki, Sakanashi, Hidenori

“…An automatic object-detection method is necessary to facilitate the efficient analysis of satellite images consisting of multispectral images. Considering that…”
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MP20-04 AUTOMATED DIAGNOSIS OF PROSTATE CANCER LOCATION AND FORM BY ARTIFICIAL INTELLIGENCE IN MULTIPARAMETRIC MRI by Oishi, Yuichiro, Kitta, Takeya, Shinohara, Nobuo, Nosato, Hirokazu, Sakanashi, Hidenori, Murakawa, Masahiro

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