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Automated region of interest retrieval and classification using spectral analysis.

Oger M, Belhomme P, Klossa J, Michels JJ, Elmoataz A - Diagn Pathol (2008)

Bottom Line: Efficient use of whole slide imaging in pathology needs automated region of interest (ROI) retrieval and classification, through the use of image analysis and data sorting tools.One possible method for data sorting uses Spectral Analysis for Dimensionality Reduction.We present some interesting results in the field of histopathology and cytohematology.

View Article: PubMed Central - HTML - PubMed

Affiliation: TRIBVN, 39 rue Louveau, Ch√Ętillon, France. m.oger@baclesse.fr

ABSTRACT
Efficient use of whole slide imaging in pathology needs automated region of interest (ROI) retrieval and classification, through the use of image analysis and data sorting tools. One possible method for data sorting uses Spectral Analysis for Dimensionality Reduction. We present some interesting results in the field of histopathology and cytohematology. In histopathology, we developed a Computer-Aided Diagnosis system applied to low-resolution images representing the totality of histological breast tumour sections. The images can be digitized directly at low resolution or be obtained from sub-sampled high-resolution virtual slides. Spectral Analysis is used (1) for image segmentation (stroma, tumour epithelium), by determining a "distance" between all the images of the database, (2) for choosing representative images and characteristic patterns of each histological type in order to index them, and (3) for visualizing images or features similar to a sample provided by the pathologist. In cytohematology, we studied a blood smear virtual slide acquired through high resolution oil scanning and Spectral Analysis is used to sort selected nucleated blood cell classes so that the pathologist may easily focus on specific classes whose morphology could then be studied more carefully or which can be analyzed through complementary instruments, like Multispectral Imaging or Raman MicroSpectroscopy.

No MeSH data available.


Related in: MedlinePlus

Result of isolated white blood cell base "segmentation" by spectral analysis: (a) visualization of the data sorting (lymphocytes are shown in blue) allowing the partition of (b) the base of isolated cells, (c) view of isolated cells sorted by spectral analysis.
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Figure 4: Result of isolated white blood cell base "segmentation" by spectral analysis: (a) visualization of the data sorting (lymphocytes are shown in blue) allowing the partition of (b) the base of isolated cells, (c) view of isolated cells sorted by spectral analysis.

Mentions: For this application, spectral analysis was used to "segment", by data sorting, the image base of isolated blood cells into two classes: polymorphonuclear cells and lymphocytes (Figure 4).


Automated region of interest retrieval and classification using spectral analysis.

Oger M, Belhomme P, Klossa J, Michels JJ, Elmoataz A - Diagn Pathol (2008)

Result of isolated white blood cell base "segmentation" by spectral analysis: (a) visualization of the data sorting (lymphocytes are shown in blue) allowing the partition of (b) the base of isolated cells, (c) view of isolated cells sorted by spectral analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2500116&req=5

Figure 4: Result of isolated white blood cell base "segmentation" by spectral analysis: (a) visualization of the data sorting (lymphocytes are shown in blue) allowing the partition of (b) the base of isolated cells, (c) view of isolated cells sorted by spectral analysis.
Mentions: For this application, spectral analysis was used to "segment", by data sorting, the image base of isolated blood cells into two classes: polymorphonuclear cells and lymphocytes (Figure 4).

Bottom Line: Efficient use of whole slide imaging in pathology needs automated region of interest (ROI) retrieval and classification, through the use of image analysis and data sorting tools.One possible method for data sorting uses Spectral Analysis for Dimensionality Reduction.We present some interesting results in the field of histopathology and cytohematology.

View Article: PubMed Central - HTML - PubMed

Affiliation: TRIBVN, 39 rue Louveau, Ch√Ętillon, France. m.oger@baclesse.fr

ABSTRACT
Efficient use of whole slide imaging in pathology needs automated region of interest (ROI) retrieval and classification, through the use of image analysis and data sorting tools. One possible method for data sorting uses Spectral Analysis for Dimensionality Reduction. We present some interesting results in the field of histopathology and cytohematology. In histopathology, we developed a Computer-Aided Diagnosis system applied to low-resolution images representing the totality of histological breast tumour sections. The images can be digitized directly at low resolution or be obtained from sub-sampled high-resolution virtual slides. Spectral Analysis is used (1) for image segmentation (stroma, tumour epithelium), by determining a "distance" between all the images of the database, (2) for choosing representative images and characteristic patterns of each histological type in order to index them, and (3) for visualizing images or features similar to a sample provided by the pathologist. In cytohematology, we studied a blood smear virtual slide acquired through high resolution oil scanning and Spectral Analysis is used to sort selected nucleated blood cell classes so that the pathologist may easily focus on specific classes whose morphology could then be studied more carefully or which can be analyzed through complementary instruments, like Multispectral Imaging or Raman MicroSpectroscopy.

No MeSH data available.


Related in: MedlinePlus