A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases

The digitization of pathology departments in hospitals around the world is now a reality. The current commercial solutions applied to digitize histopathological samples consist of a robotic microscope with an RGB-type camera attached to it. This technology is very limited in terms of information captured, as it only works with three spectral bands of the visible electromagnetic spectrum. Therefore, we present an automated system that combines RGB and hyperspectral technology. Throughout this work, the hardware of the system and its components are described along with the developed software and a working methodology to ensure the correct capture of histopathological samples. The software is integrated by the controller of the microscope, which features an autofocus functionality, whole slide scanning with a stitching algorithm, and hyperspectral scanning functionality. As a reference, the time to capture and process a complete sample with 20 regions of high biological interest using the proposed method is estimated at a maximum of 79 min, reducing the time required by a manual operator by at least three times. Both hardware and software can be easily adapted to other systems that might benefit from the advantages of hyperspectral technology.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2024-08-30
DOI
https://doi.org/10.3390/s24175654
Citations
3
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.96

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases

Miguel Chavarrías, Fernando Pescador, Gonzalo Rosa, Ricardo Gargini et al.
3 citations
Sensors
Image Processing Techniques and Applications
0.96
article

A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases

Miguel Chavarrías, Fernando Pescador, Gonzalo Rosa, Ricardo Gargini, Manuel Villa, Sara Hiller-Vallina
article en
3 citations

Abstract

The digitization of pathology departments in hospitals around the world is now a reality. The current commercial solutions applied to digitize histopathological samples consist of a robotic microscope with an RGB-type camera attached to it. This technology is very limited in terms of information captured, as it only works with three spectral bands of the visible electromagnetic spectrum. Therefore, we present an automated system that combines RGB and hyperspectral technology. Throughout this work, the hardware of the system and its components are described along with the developed software and a working methodology to ensure the correct capture of histopathological samples. The software is integrated by the controller of the microscope, which features an autofocus functionality, whole slide scanning with a stitching algorithm, and hyperspectral scanning functionality. As a reference, the time to capture and process a complete sample with 20 regions of high biological interest using the proposed method is estimated at a maximum of 79 min, reducing the time required by a manual operator by at least three times. Both hardware and software can be easily adapted to other systems that might benefit from the advantages of hyperspectral technology.

SensorsVol. 24(17)
Hospital Universitario 12 De Octubre (ES), Universidad Politécnica de Madrid (ES), Software (Spain) (ES)
Ministerio de Ciencia e Innovación
Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Image Processing Techniques and Applications
0.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases — Miguel Chavarrías, Fernando Pescador, et al. · Sensors (2024) | TGRS Research Map | TGRS