Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs
In thoraco-laparoscopic surgery, the identification of a bleeding source is recognized as one of the most important issues with hemostasis during operation. However, previously proposed techniques are only capable of detecting an approximate bleeding region, not the precise location itself. To devel...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Array |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005623000334 |
| _version_ | 1827813731100262400 |
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| author | Maina Sogabe Kaoru Ishikawa Toshihiro Takamatsu Koh Takeuchi Takahiro Kanno Koji Fujimoto Tetsuro Miyazaki Toshihiro Kawase Toshihiko Sato Kenji Kawashima |
| author_facet | Maina Sogabe Kaoru Ishikawa Toshihiro Takamatsu Koh Takeuchi Takahiro Kanno Koji Fujimoto Tetsuro Miyazaki Toshihiro Kawase Toshihiko Sato Kenji Kawashima |
| author_sort | Maina Sogabe |
| collection | DOAJ |
| description | In thoraco-laparoscopic surgery, the identification of a bleeding source is recognized as one of the most important issues with hemostasis during operation. However, previously proposed techniques are only capable of detecting an approximate bleeding region, not the precise location itself. To develop a system which can accurately localize a bleeding source, post-bleeding images and their corresponding bleeding source information may be required. However, to pinpoint bleeding sources from actual thoraco-laparoscopic surgery images is no easy task even for an experienced surgeon. In previous studies, a surgeon could only provide rectangular region information around a bleeding source. To address the problem, we have developed a mimicking device that simulates bleeding from a vessel on an artificial organ for obtaining bleeding images and precise bleeding source information at the same time. Using this information, we constructed a Generator that can associate a bleeding image with the corresponding bleeding source by using Pix2Pix and created a “bleeding alert map (BAM)” which concerns the Predicted intensity of bleeding source in the endoscopic view. The Generator successfully created BAMs from ex vivo lung bleeding images as well as actual organ bleeding images captured in thoracoscopic surgeries. The results showed that the BAM Generator constructed only by using the data from the mimicking device was effective in processing bleeding images from actual organs to identify bleeding sources. The proposed system may be utilized during endoscopic surgery to present a BAM which carries important information for hemostasis. |
| first_indexed | 2024-03-11T23:35:15Z |
| format | Article |
| id | doaj.art-b73d693eeea14d8fa8088fb080ff0528 |
| institution | Directory Open Access Journal |
| issn | 2590-0056 |
| language | English |
| last_indexed | 2024-03-11T23:35:15Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Array |
| spelling | doaj.art-b73d693eeea14d8fa8088fb080ff05282023-09-20T04:21:47ZengElsevierArray2590-00562023-09-0119100308Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organsMaina Sogabe0Kaoru Ishikawa1Toshihiro Takamatsu2Koh Takeuchi3Takahiro Kanno4Koji Fujimoto5Tetsuro Miyazaki6Toshihiro Kawase7Toshihiko Sato8Kenji Kawashima9The Department of Information Physics and Computing, The University of Tokyo, JapanThe Department of Information Physics and Computing, The University of Tokyo, JapanThe department of Exploratory Oncology Research & Clinical Trial Center, National Cancer Center and Research Institute for Biomedical Sciences,Tokyo University of Science, JapanGraduate School of Informatics, Kyoto University, JapanRiverfield Inc., JapanReal World Data Research and Development, Graduate School of Medicine, Kyoto University, JapanThe Department of Information Physics and Computing, The University of Tokyo, JapanDepartment of Information and Communication Engineering, School of Engineering, Tokyo Denki University, Tokyo, JapanThe Department of medicine, Fukuoka University, JapanThe Department of Information Physics and Computing, The University of Tokyo, Japan; Corresponding author.In thoraco-laparoscopic surgery, the identification of a bleeding source is recognized as one of the most important issues with hemostasis during operation. However, previously proposed techniques are only capable of detecting an approximate bleeding region, not the precise location itself. To develop a system which can accurately localize a bleeding source, post-bleeding images and their corresponding bleeding source information may be required. However, to pinpoint bleeding sources from actual thoraco-laparoscopic surgery images is no easy task even for an experienced surgeon. In previous studies, a surgeon could only provide rectangular region information around a bleeding source. To address the problem, we have developed a mimicking device that simulates bleeding from a vessel on an artificial organ for obtaining bleeding images and precise bleeding source information at the same time. Using this information, we constructed a Generator that can associate a bleeding image with the corresponding bleeding source by using Pix2Pix and created a “bleeding alert map (BAM)” which concerns the Predicted intensity of bleeding source in the endoscopic view. The Generator successfully created BAMs from ex vivo lung bleeding images as well as actual organ bleeding images captured in thoracoscopic surgeries. The results showed that the BAM Generator constructed only by using the data from the mimicking device was effective in processing bleeding images from actual organs to identify bleeding sources. The proposed system may be utilized during endoscopic surgery to present a BAM which carries important information for hemostasis.http://www.sciencedirect.com/science/article/pii/S2590005623000334Bleeding source estimationEndoscopic surgeryPix2PixTraining data from mimicking organs |
| spellingShingle | Maina Sogabe Kaoru Ishikawa Toshihiro Takamatsu Koh Takeuchi Takahiro Kanno Koji Fujimoto Tetsuro Miyazaki Toshihiro Kawase Toshihiko Sato Kenji Kawashima Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs Array Bleeding source estimation Endoscopic surgery Pix2Pix Training data from mimicking organs |
| title | Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs |
| title_full | Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs |
| title_fullStr | Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs |
| title_full_unstemmed | Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs |
| title_short | Bleeding alert map (BAM): The identification method of the bleeding source in real organs using datasets made on mimicking organs |
| title_sort | bleeding alert map bam the identification method of the bleeding source in real organs using datasets made on mimicking organs |
| topic | Bleeding source estimation Endoscopic surgery Pix2Pix Training data from mimicking organs |
| url | http://www.sciencedirect.com/science/article/pii/S2590005623000334 |
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