SpatialVisVR: An Immersive, Multiplexed Medical Image Viewer With Contextual Similar-Patient Search

Fuente: arXiv
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Hauptverfasser: Veerla, Jai Prakash, Guttikonda, Partha Sai, Hajighasemi, Amir, Saurav, Jillur Rahman, Darji, Aarti, Reynolds, Cody T., Mohamed, Mohamed, Nasr, Mohammad S., Shang, Helen H., Luber, Jacob M.
Format: Preprint
Veröffentlicht: 2024
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author Veerla, Jai Prakash
Guttikonda, Partha Sai
Hajighasemi, Amir
Saurav, Jillur Rahman
Darji, Aarti
Reynolds, Cody T.
Mohamed, Mohamed
Nasr, Mohammad S.
Shang, Helen H.
Luber, Jacob M.
author_facet Veerla, Jai Prakash
Guttikonda, Partha Sai
Hajighasemi, Amir
Saurav, Jillur Rahman
Darji, Aarti
Reynolds, Cody T.
Mohamed, Mohamed
Nasr, Mohammad S.
Shang, Helen H.
Luber, Jacob M.
contents In contemporary pathology, multiplexed immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) present both significant opportunities and challenges. These methodologies shed light on intricate tumor microenvironment interactions, emphasizing the need for intuitive visualization tools to analyze vast biological datasets effectively. As electronic health records (EHR) proliferate and physicians face increasing information overload, the integration of advanced technologies becomes imperative. SpatialVisVR emerges as a versatile VR platform tailored for comparing medical images, with adaptability for data privacy on embedded hardware. Clinicians can capture pathology slides in real-time via mobile devices, leveraging SpatialVisVR's deep learning algorithm to match and display similar mIF images. This interface supports the manipulation of up to 100 multiplexed protein channels, thereby assisting in immuno-oncology decision-making. Ultimately, SpatialVisVR aims to streamline diagnostic processes, advocating for a comprehensive and efficient approach to immuno-oncology research and treatment.
format Preprint
id arxiv_https___arxiv_org_abs_2401_02882
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SpatialVisVR: An Immersive, Multiplexed Medical Image Viewer With Contextual Similar-Patient Search
Veerla, Jai Prakash
Guttikonda, Partha Sai
Hajighasemi, Amir
Saurav, Jillur Rahman
Darji, Aarti
Reynolds, Cody T.
Mohamed, Mohamed
Nasr, Mohammad S.
Shang, Helen H.
Luber, Jacob M.
Human-Computer Interaction
Tissues and Organs
In contemporary pathology, multiplexed immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) present both significant opportunities and challenges. These methodologies shed light on intricate tumor microenvironment interactions, emphasizing the need for intuitive visualization tools to analyze vast biological datasets effectively. As electronic health records (EHR) proliferate and physicians face increasing information overload, the integration of advanced technologies becomes imperative. SpatialVisVR emerges as a versatile VR platform tailored for comparing medical images, with adaptability for data privacy on embedded hardware. Clinicians can capture pathology slides in real-time via mobile devices, leveraging SpatialVisVR's deep learning algorithm to match and display similar mIF images. This interface supports the manipulation of up to 100 multiplexed protein channels, thereby assisting in immuno-oncology decision-making. Ultimately, SpatialVisVR aims to streamline diagnostic processes, advocating for a comprehensive and efficient approach to immuno-oncology research and treatment.
title SpatialVisVR: An Immersive, Multiplexed Medical Image Viewer With Contextual Similar-Patient Search
topic Human-Computer Interaction
Tissues and Organs
url https://arxiv.org/abs/2401.02882