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Deep Vision: Near-infrared imaging and machine learning can identify hidden tumors

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IMAGE: The machine learning technique developed by Dr. Takemura and team could distinguish tumor tissue from healthy tissue in ex vivo images of resected tumors, with 86% accuracy.
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Credit: Hiroshi Takemura from Tokyo University of Science
Tumors can be damaging to surrounding blood vessels and tissues even if they re benign. If they re malignant, they re aggressive and sneaky, and often irrevocably damaging. In the latter case, early detection is key to treatment and recovery. But such detection can sometimes require advanced imaging technology, beyond what is available commercially today.
For instance, some tumors occur deep inside organs and tissues, covered by a mucosal layer, which makes it difficult for scientists to directly observe them with standard methods like endoscopy (which inserts a small camera into a patient s body via a thin tube) or reach them during biopsies. In particular, gastrointestinal stromal tumors (GISTs) ....

Hiroaki Ikematsu , Hideo Yokotad Eng , Tomonori Yano , Daiki Sato , Kohei Soga , Masao Kamimura , Hideo Yokota , Yuichi Kitagawa , Hiroshi Takemura , Naoki Hosokawa , Takeshi Kuwata , Tomohiro Kadota , Masakazu Umezawa , Takahiro Kinoshita , Toshihiro Takamatsu , Kosuke Maeda , Kazuhiro Kaneko , Kyohei Okubo , Tetsuo Akimoto , Course Of Advanced Clinical Research Cancer , Division Of Radiation Oncology , Department Of Gastric Surgery , Juntendo University Graduate School Of Medicine , Research Institute For Biomedical Sciences , Department Of Mechanical Engineering , National Cancer Center Hospital ,