2017 Winter Project Week/HyperspectralOpht - Revision history

Shong: /* Acknowledgement */

2017-01-13T16:05:58Z

Acknowledgement

2017-01-13T16:03:02Z

2017-01-13T15:24:05Z

2017-01-13T14:41:08Z

Project Description

2017-01-13T14:40:14Z

Project Description

2017-01-12T19:36:03Z

Project Description

2017-01-10T21:21:01Z

Project Description

2017-01-10T21:11:38Z

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2017-01-09T16:23:09Z

Project Description

← Older revision		Revision as of 16:05, 13 January 2017
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	==Acknowledgement==		==Acknowledgement==
−	We would like to thank Dr. Thomas Ach (University Hospital Würzburg, Germany) for the contribution on the data and the project.	+	We would like to thank Dr. Thomas Ach (University Hospital Würzburg, Germany) for the significant contribution on the data and the project.

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 File:LSM_SIM_Zoomed.png|link=File:LSM_SIM_Zoomed.png|Individual granules (Lipofuscin (bright) and Melano-lipofuscin (dark)) in a zoomed view of LSM and SIM.
 File:MultiVolExp Zoomed Plot.png|link=File:MultiVolExp Zoomed Plot.png|Hyperspectral Information of pre-segmented individual granule (LF).
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 File:Segmentation_Cells.png|link=File:Segmentation_Cells.png|Cell segmentation on 3D SIM data. The segmentation mask is overlayed on 4D LSM data for spectral analysis.
 File:LSM_SIM_Zoomed.png|link=File:LSM_SIM_Zoomed.png|Individual granules (Lipofuscin (bright) and Melano-lipofuscin (dark)) in a zoomed view of LSM and SIM.
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 ** With a converted series of 3D data, MultiVolume explorer offered a basic analysis tool for hyperspectral data.
 ** Label statistics or segmentation need to be added in the future
 * Registration

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 <!-- Progress and Next steps bullet points (fill out at the end of project week -->
 * Hyperspectral Analysis
-** Investigated Multivolume Explorer to analyze hyperspectral data
+** Implemented a module to convert 4D LSM data to a series of 3D data compatible to MultiVolume Explorer
 *** Need to convert the 4D data recognizable to Multivolume importer (A series of 3D data)
 * Segmentation
 ** Watershed segmentation on 3D hi-res image data (WASP) was not successful.
 ** Editor/Segmentation Editor worked good on slice-by-slice segmentation
-** Need to explore 3D segmentation capability of Editor/Segmentation Editor
+** Will investigate more on 3D segmentation capability of Slicer with possible collaboration with other groups.

← Older revision		Revision as of 21:11, 10 January 2017
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	==Acknowledgement==		==Acknowledgement==
−	We would like to thank Dr. Thomas Ach (~~MD,~~ University of Würzburg) for the contribution on the data and the project.	+	We would like to thank Dr. Thomas Ach (University Hospital Würzburg, Germany) for the contribution on the data and the project.

← Older revision		Revision as of 21:10, 10 January 2017
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	==Background and References==		==Background and References==
	<!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->		<!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->
		+
		+	==Acknowledgement==
		+	We would like to thank Dr. Thomas Ach (MD, University of Würzburg) for the contribution on the data and the project.

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 This project aims to offer a tool which makes use of 3D/4D ophthalmology data in different modalities to extract information which can compensate each other for richer analysis.
 D high resolution data (high resolution structured illumination microscopy, SIM) displays individual cells with sharp boundaries which are hard to be localized in 4D hyperspectral data (confocal multispectral laser scanning microscopy, LSM) because of low resolution.
-The tool that we want to provide to users should offer image processing modules, such as, co-registration between SIM and LSM data, segmentation on SIM and mapping the segmentation label from SIM to LSM to analyze spectral information of each cell.
+The tool that we want to provide to users should offer image processing modules, such as, co-registration between SIM and LSM data, segmentation on SIM and mapping the segmentation label from SIM to LSM to analyze spectral information of each granule. The examination of spectral characteristics and statistics of granules, related with age and disease progress might reveal metabolism in human retina physiology.
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