Literature DB >> 35028877

Artificial intelligence for nuclear medicine in oncology.

Kenji Hirata1,2,3, Hiroyuki Sugimori4, Noriyuki Fujima5,6, Takuya Toyonaga7, Kohsuke Kudo5,8,6,9.   

Abstract

As in all other medical fields, artificial intelligence (AI) is increasingly being used in nuclear medicine for oncology. There are many articles that discuss AI from the viewpoint of nuclear medicine, but few focus on nuclear medicine from the viewpoint of AI. Nuclear medicine images are characterized by their low spatial resolution and high quantitativeness. It is noted that AI has been used since before the emergence of deep learning. AI can be divided into three categories by its purpose: (1) assisted interpretation, i.e., computer-aided detection (CADe) or computer-aided diagnosis (CADx). (2) Additional insight, i.e., AI provides information beyond the radiologist's eye, such as predicting genes and prognosis from images. It is also related to the field called radiomics/radiogenomics. (3) Augmented image, i.e., image generation tasks. To apply AI to practical use, harmonization between facilities and the possibility of black box explanations need to be resolved.
© 2021. The Author(s) under exclusive licence to The Japanese Society of Nuclear Medicine.

Entities:  

Keywords:  Artificial intelligence; Deep learning; Nuclear medicine; Oncology; Radiomics

Mesh:

Year:  2022        PMID: 35028877     DOI: 10.1007/s12149-021-01693-6

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  63 in total

Review 1.  Deep learning.

Authors:  Yann LeCun; Yoshua Bengio; Geoffrey Hinton
Journal:  Nature       Date:  2015-05-28       Impact factor: 49.962

2.  Prognostic impact of bone metastatic volume beyond vertebrae and pelvis in patients with metastatic hormone-sensitive prostate cancer.

Authors:  Kotaro Suzuki; Yasuyoshi Okamura; Takuto Hara; Tomoaki Terakawa; Junya Furukawa; Kenichi Harada; Nobuyuki Hinata; Masato Fujisawa
Journal:  Int J Clin Oncol       Date:  2021-05-28       Impact factor: 3.402

Review 3.  Bone scan index: A new biomarker of bone metastasis in patients with prostate cancer.

Authors:  Kenichi Nakajima; Lars Edenbrandt; Atsushi Mizokami
Journal:  Int J Urol       Date:  2017-05-26       Impact factor: 3.369

Review 4.  Current status of robot-assisted minimally invasive esophagectomy: what is the real benefit?

Authors:  Jun Kanamori; Masayuki Watanabe; Suguru Maruyama; Yasukazu Kanie; Daisuke Fujiwara; Kei Sakamoto; Akihiko Okamura; Yu Imamura
Journal:  Surg Today       Date:  2021-12-01       Impact factor: 2.540

5.  Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: a retrospective clinical validation study.

Authors:  Daiju Ueda; Akira Yamamoto; Akitoshi Shimazaki; Shannon Leigh Walston; Toshimasa Matsumoto; Nobuhiro Izumi; Takuma Tsukioka; Hiroaki Komatsu; Hidetoshi Inoue; Daijiro Kabata; Noritoshi Nishiyama; Yukio Miki
Journal:  BMC Cancer       Date:  2021-10-18       Impact factor: 4.430

6.  Artificial intelligence versus expert endoscopists for diagnosis of gastric cancer in patients who have undergone upper gastrointestinal endoscopy.

Authors:  Ryota Niikura; Tomonori Aoki; Satoki Shichijo; Atsuo Yamada; Takuya Kawahara; Yusuke Kato; Yoshihiro Hirata; Yoku Hayakawa; Nobumi Suzuki; Masanori Ochi; Toshiaki Hirasawa; Tomohiro Tada; Takashi Kawai; Kazuhiko Koike
Journal:  Endoscopy       Date:  2022-05-04       Impact factor: 9.776

Review 7.  Automated deep learning in ophthalmology: AI that can build AI.

Authors:  Ciara O'Byrne; Abdallah Abbas; Edward Korot; Pearse A Keane
Journal:  Curr Opin Ophthalmol       Date:  2021-09-01       Impact factor: 3.761

8.  Prognostic value of an automated bone scan index for men with metastatic castration-resistant prostate cancer treated with cabazitaxel.

Authors:  Koichi Uemura; Yasuhide Miyoshi; Takashi Kawahara; Jikuya Ryosuke; Daisuke Yamashita; Shuko Yoneyama; Yumiko Yokomizo; Kazuki Kobayashi; Takeshi Kishida; Masahiro Yao; Hiroji Uemura
Journal:  BMC Cancer       Date:  2018-05-02       Impact factor: 4.430

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  2 in total

1.  Medical Radiation Exposure Reduction in PET via Super-Resolution Deep Learning Model.

Authors:  Takaaki Yoshimura; Atsushi Hasegawa; Shoki Kogame; Keiichi Magota; Rina Kimura; Shiro Watanabe; Kenji Hirata; Hiroyuki Sugimori
Journal:  Diagnostics (Basel)       Date:  2022-03-31

2.  Diagnosis of Parkinson syndrome and Lewy-body disease using 123I-ioflupane images and a model with image features based on machine learning.

Authors:  Kenichi Nakajima; Shintaro Saito; Zhuoqing Chen; Junji Komatsu; Koji Maruyama; Naoki Shirasaki; Satoru Watanabe; Anri Inaki; Kenjiro Ono; Seigo Kinuya
Journal:  Ann Nucl Med       Date:  2022-07-07       Impact factor: 2.258

  2 in total

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