Search Results - "Urushibara, Aiko"

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  1. 1

    Diagnosing uterine cervical cancer on a single T2-weighted image: Comparison between deep learning versus radiologists by Urushibara, Aiko, Saida, Tsukasa, Mori, Kensaku, Ishiguro, Toshitaka, Sakai, Masafumi, Masuoka, Souta, Satoh, Toyomi, Masumoto, Tomohiko

    Published in European journal of radiology (01-02-2021)
    “…•A deep learning model using convolutional neural networks (DCNN) can diagnose uterine cervical cancer on a T2-weighted image.•The DCNN model, built from less…”
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    Journal Article
  2. 2

    The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists by Urushibara, Aiko, Saida, Tsukasa, Mori, Kensaku, Ishiguro, Toshitaka, Inoue, Kei, Masumoto, Tomohiko, Satoh, Toyomi, Nakajima, Takahito

    Published in BMC medical imaging (30-04-2022)
    “…To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial…”
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    Journal Article
  3. 3

    Preoperative diagnosis of a torsioned accessory spleen by Yoshida, Miki, Saida, Tsukasa, Masuoka, Souta, Urushibara, Aiko, Chiba, Fumiko, Masumoto, Kouji

    Published in Journal of medical ultrasound (01-04-2021)
    “…We report a case of a 12-year-old boy with an accessory spleen torsion. He presented with left-sided abdominal pain after trauma. A 4 cm oval mass without…”
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    Journal Article
  4. 4

    Pulmonary arterial pseudoaneurysm as an unusual complication of pulmonary actinomycosis: Two case reports by Urushibara, Aiko, Hoshiai, Sodai, Koyama, Ken, Kiyoshima, Moriyuki, Iijima, Tatsuo, Nakajima, Takahito

    Published in Radiology case reports (01-01-2023)
    “…We report 2 cases of pulmonary actinomycosis complicated by a pseudoaneurysm. In Case 1, a 67-year-old man visited a hospital 7 months ago because of…”
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    Journal Article
  5. 5

    Differentiation of carcinosarcoma from endometrial carcinoma on magnetic resonance imaging using deep learning by Saida, Tsukasa, Mori, Kensaku, Hoshiai, Sodai, Sakai, Masafumi, Urushibara, Aiko, Ishiguro, Toshitaka, Satoh, Toyomi, Nakajima, Takahito

    Published in Polish journal of radiology (2022)
    “…PurposeTo verify whether deep learning can be used to differentiate between carcinosarcomas (CSs) and endometrial carcinomas (ECs) using several magnetic…”
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    Journal Article
  6. 6

    Diagnosing Ovarian Cancer on MRI: A Preliminary Study Comparing Deep Learning and Radiologist Assessments by Saida, Tsukasa, Mori, Kensaku, Hoshiai, Sodai, Sakai, Masafumi, Urushibara, Aiko, Ishiguro, Toshitaka, Minami, Manabu, Satoh, Toyomi, Nakajima, Takahito

    Published in Cancers (16-02-2022)
    “…This study aimed to compare deep learning with radiologists' assessments for diagnosing ovarian carcinoma using MRI. This retrospective study included 194…”
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    Journal Article
  7. 7

    Prediction of testicular atrophy based on sonographic findings immediately after successful manual detorsion by Hosokawa, Takahiro, Urushibara, Aiko, Tanami, Yutaka, Sato, Yumiko, Ishimaru, Tetsuya, Ohashi, Kensuke, Kawashima, Hiroshi, Oguma, Eiji

    “…Purpose To investigate and determine the sonographic findings obtained from manually distorted testes to predict testicular atrophy following manual detorsion…”
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