Limits...
Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis.

Iakovidis DK, Goudas T, Smailis C, Maglogiannis I - ScientificWorldJournal (2014)

Bottom Line: In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system.However a tool for detecting and quantifying the disease is not yet available.The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics and Computer Technology, Technological Educational Institute of Lamia, 35100 Lamia, Greece.

ABSTRACT
Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD) systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

Show MeSH

Related in: MedlinePlus

Example of segmentation and annotation of the pathogenic kidney biopsy image illustrated in Figure 1(b) using Ratsnake. (a) Pathogenic glomerulus region of Figure 1(b). (b) Quick rough freehand initial user annotation. (c) Polygon user annotation with landmarks automatically derived from the freehand annotation. (d) T(Bd). (e) PIcs defined by (2). (f) Segmented ROI using (2) with f1(I) and image-specific snake parameters. However, such an image-specific approach would not be suitable for a CAD system capable of coping with annotation of any images of this kind.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3926425&req=5

fig2: Example of segmentation and annotation of the pathogenic kidney biopsy image illustrated in Figure 1(b) using Ratsnake. (a) Pathogenic glomerulus region of Figure 1(b). (b) Quick rough freehand initial user annotation. (c) Polygon user annotation with landmarks automatically derived from the freehand annotation. (d) T(Bd). (e) PIcs defined by (2). (f) Segmented ROI using (2) with f1(I) and image-specific snake parameters. However, such an image-specific approach would not be suitable for a CAD system capable of coping with annotation of any images of this kind.

Mentions: The segmentation framework of Ratsnake considers that the user initially provides a quick, rough, outline of a ROI (Figure 2(a)) which is subsequently refined by a parametric active contour model, also referred to as snake [32] (Figure 2(b)). This snake-based framework is now enhanced by the introduction of a force field generated by a machine learning-based method. This force field is implemented as a Ratsnake plugin and attracts the deformable contour towards the boundaries of a target classified ROI. The details of this approach are provided in the rest of this section.


Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis.

Iakovidis DK, Goudas T, Smailis C, Maglogiannis I - ScientificWorldJournal (2014)

Example of segmentation and annotation of the pathogenic kidney biopsy image illustrated in Figure 1(b) using Ratsnake. (a) Pathogenic glomerulus region of Figure 1(b). (b) Quick rough freehand initial user annotation. (c) Polygon user annotation with landmarks automatically derived from the freehand annotation. (d) T(Bd). (e) PIcs defined by (2). (f) Segmented ROI using (2) with f1(I) and image-specific snake parameters. However, such an image-specific approach would not be suitable for a CAD system capable of coping with annotation of any images of this kind.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3926425&req=5

fig2: Example of segmentation and annotation of the pathogenic kidney biopsy image illustrated in Figure 1(b) using Ratsnake. (a) Pathogenic glomerulus region of Figure 1(b). (b) Quick rough freehand initial user annotation. (c) Polygon user annotation with landmarks automatically derived from the freehand annotation. (d) T(Bd). (e) PIcs defined by (2). (f) Segmented ROI using (2) with f1(I) and image-specific snake parameters. However, such an image-specific approach would not be suitable for a CAD system capable of coping with annotation of any images of this kind.
Mentions: The segmentation framework of Ratsnake considers that the user initially provides a quick, rough, outline of a ROI (Figure 2(a)) which is subsequently refined by a parametric active contour model, also referred to as snake [32] (Figure 2(b)). This snake-based framework is now enhanced by the introduction of a force field generated by a machine learning-based method. This force field is implemented as a Ratsnake plugin and attracts the deformable contour towards the boundaries of a target classified ROI. The details of this approach are provided in the rest of this section.

Bottom Line: In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system.However a tool for detecting and quantifying the disease is not yet available.The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

View Article: PubMed Central - PubMed

Affiliation: Department of Informatics and Computer Technology, Technological Educational Institute of Lamia, 35100 Lamia, Greece.

ABSTRACT
Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD) systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

Show MeSH
Related in: MedlinePlus