Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT
Pathological features are the gold standard for tumor diagnosis, guiding treatment and prognosis. However, standard histopathological process is labor-intensive and time-consuming, while frozen sections have lower accuracy. Dynamic full-field optical coherence tomography (D-FFOCT) offers rapid histo...
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| creator | Yin, Zichen He, Bin Ying, Yuzhe Zhang, Shuwei Yang, Panqi Chen, Zhengyu Hu, Zhangwei Shi, Yejiong Xue, Ruizhi Wang, Chengming Wang, Shu Wang, Guihuai Xue, Ping |
| description | Pathological features are the gold standard for tumor diagnosis, guiding
treatment and prognosis. However, standard histopathological process is
labor-intensive and time-consuming, while frozen sections have lower accuracy.
Dynamic full-field optical coherence tomography (D-FFOCT) offers rapid
histologic information by measuring the subcellular dynamics of fresh,
unprocessed tissues. However, D-FFOCT images suffer from abrupt shifts in hue
and brightness, which is confusing for pathologists and diminish their
interpretability and reliability. Here, we present active phase
modulation-assisted D-FFOCT (APMD-FFOCT) to improve the imaging stability and
enhance the contrast of static tissues. This enables us to further employ an
unsupervised deep learning to convert APMD-FFOCT images into virtual
hematoxylin and eosin (H&E) stained images for the first time.
Three-dimensional (3D) virtual H&E-stained images have been obtained at a
scanning rate of 1 frame per second, as demonstrated in cancer diagnosis for
human central nervous system and breast. The results prove that this new method
will play a unique and important role in intraoperative histology. |
| doi_str_mv | 10.48550/arxiv.2404.19641 |
| format | Article |
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treatment and prognosis. However, standard histopathological process is
labor-intensive and time-consuming, while frozen sections have lower accuracy.
Dynamic full-field optical coherence tomography (D-FFOCT) offers rapid
histologic information by measuring the subcellular dynamics of fresh,
unprocessed tissues. However, D-FFOCT images suffer from abrupt shifts in hue
and brightness, which is confusing for pathologists and diminish their
interpretability and reliability. Here, we present active phase
modulation-assisted D-FFOCT (APMD-FFOCT) to improve the imaging stability and
enhance the contrast of static tissues. This enables us to further employ an
unsupervised deep learning to convert APMD-FFOCT images into virtual
hematoxylin and eosin (H&E) stained images for the first time.
Three-dimensional (3D) virtual H&E-stained images have been obtained at a
scanning rate of 1 frame per second, as demonstrated in cancer diagnosis for
human central nervous system and breast. The results prove that this new method
will play a unique and important role in intraoperative histology.</description><identifier>DOI: 10.48550/arxiv.2404.19641</identifier><language>eng</language><subject>Physics - Biological Physics ; Physics - Medical Physics ; Physics - Optics</subject><creationdate>2024-04</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2404.19641$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2404.19641$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Yin, Zichen</creatorcontrib><creatorcontrib>He, Bin</creatorcontrib><creatorcontrib>Ying, Yuzhe</creatorcontrib><creatorcontrib>Zhang, Shuwei</creatorcontrib><creatorcontrib>Yang, Panqi</creatorcontrib><creatorcontrib>Chen, Zhengyu</creatorcontrib><creatorcontrib>Hu, Zhangwei</creatorcontrib><creatorcontrib>Shi, Yejiong</creatorcontrib><creatorcontrib>Xue, Ruizhi</creatorcontrib><creatorcontrib>Wang, Chengming</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Wang, Guihuai</creatorcontrib><creatorcontrib>Xue, Ping</creatorcontrib><title>Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT</title><description>Pathological features are the gold standard for tumor diagnosis, guiding
treatment and prognosis. However, standard histopathological process is
labor-intensive and time-consuming, while frozen sections have lower accuracy.
Dynamic full-field optical coherence tomography (D-FFOCT) offers rapid
histologic information by measuring the subcellular dynamics of fresh,
unprocessed tissues. However, D-FFOCT images suffer from abrupt shifts in hue
and brightness, which is confusing for pathologists and diminish their
interpretability and reliability. Here, we present active phase
modulation-assisted D-FFOCT (APMD-FFOCT) to improve the imaging stability and
enhance the contrast of static tissues. This enables us to further employ an
unsupervised deep learning to convert APMD-FFOCT images into virtual
hematoxylin and eosin (H&E) stained images for the first time.
Three-dimensional (3D) virtual H&E-stained images have been obtained at a
scanning rate of 1 frame per second, as demonstrated in cancer diagnosis for
human central nervous system and breast. The results prove that this new method
will play a unique and important role in intraoperative histology.</description><subject>Physics - Biological Physics</subject><subject>Physics - Medical Physics</subject><subject>Physics - Optics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotjz9PwzAUxL0woMIHYOJN3RLixHaSEYWWIlXqkj16sf2oJSdBzh-Rb08oLHen0-mkH2NPPIlFIWXyguHbLXEqEhHzUgl-z9ojjhNgb8Bja31EwVrI3mBxYZrRw2l_gKsbp8EPn-vWIqCe3GKhG8zscXJDH-E4bgtrwKw9dk4DzX57ctYbuFT1A7sj9KN9_Pcdq4-HujpF58v7R_V6jlDlPGp1QgW1spAqx4K0TovM8pInJCzlrSrRlJpIqS2JHAVHmYtUbiqRyKhsx57_bm-QzVdwHYa1-YVtbrDZDw8fT-0</recordid><startdate>20240426</startdate><enddate>20240426</enddate><creator>Yin, Zichen</creator><creator>He, Bin</creator><creator>Ying, Yuzhe</creator><creator>Zhang, Shuwei</creator><creator>Yang, Panqi</creator><creator>Chen, Zhengyu</creator><creator>Hu, Zhangwei</creator><creator>Shi, Yejiong</creator><creator>Xue, Ruizhi</creator><creator>Wang, Chengming</creator><creator>Wang, Shu</creator><creator>Wang, Guihuai</creator><creator>Xue, Ping</creator><scope>GOX</scope></search><sort><creationdate>20240426</creationdate><title>Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT</title><author>Yin, Zichen ; He, Bin ; Ying, Yuzhe ; Zhang, Shuwei ; Yang, Panqi ; Chen, Zhengyu ; Hu, Zhangwei ; Shi, Yejiong ; Xue, Ruizhi ; Wang, Chengming ; Wang, Shu ; Wang, Guihuai ; Xue, Ping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a671-bc0f8fb58567a8fcc283e1910f4ef7b69ad9cff6669a47a41a57425a575affd63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Physics - Biological Physics</topic><topic>Physics - Medical Physics</topic><topic>Physics - Optics</topic><toplevel>online_resources</toplevel><creatorcontrib>Yin, Zichen</creatorcontrib><creatorcontrib>He, Bin</creatorcontrib><creatorcontrib>Ying, Yuzhe</creatorcontrib><creatorcontrib>Zhang, Shuwei</creatorcontrib><creatorcontrib>Yang, Panqi</creatorcontrib><creatorcontrib>Chen, Zhengyu</creatorcontrib><creatorcontrib>Hu, Zhangwei</creatorcontrib><creatorcontrib>Shi, Yejiong</creatorcontrib><creatorcontrib>Xue, Ruizhi</creatorcontrib><creatorcontrib>Wang, Chengming</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Wang, Guihuai</creatorcontrib><creatorcontrib>Xue, Ping</creatorcontrib><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yin, Zichen</au><au>He, Bin</au><au>Ying, Yuzhe</au><au>Zhang, Shuwei</au><au>Yang, Panqi</au><au>Chen, Zhengyu</au><au>Hu, Zhangwei</au><au>Shi, Yejiong</au><au>Xue, Ruizhi</au><au>Wang, Chengming</au><au>Wang, Shu</au><au>Wang, Guihuai</au><au>Xue, Ping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT</atitle><date>2024-04-26</date><risdate>2024</risdate><abstract>Pathological features are the gold standard for tumor diagnosis, guiding
treatment and prognosis. However, standard histopathological process is
labor-intensive and time-consuming, while frozen sections have lower accuracy.
Dynamic full-field optical coherence tomography (D-FFOCT) offers rapid
histologic information by measuring the subcellular dynamics of fresh,
unprocessed tissues. However, D-FFOCT images suffer from abrupt shifts in hue
and brightness, which is confusing for pathologists and diminish their
interpretability and reliability. Here, we present active phase
modulation-assisted D-FFOCT (APMD-FFOCT) to improve the imaging stability and
enhance the contrast of static tissues. This enables us to further employ an
unsupervised deep learning to convert APMD-FFOCT images into virtual
hematoxylin and eosin (H&E) stained images for the first time.
Three-dimensional (3D) virtual H&E-stained images have been obtained at a
scanning rate of 1 frame per second, as demonstrated in cancer diagnosis for
human central nervous system and breast. The results prove that this new method
will play a unique and important role in intraoperative histology.</abstract><doi>10.48550/arxiv.2404.19641</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Physics - Biological Physics Physics - Medical Physics Physics - Optics |
| title | Fast and label-free 3D virtual H&E histology via active modulation-assisted dynamic full-field OCT |
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