Journal: Frontiers in Bioengineering and Biotechnology

Article Title: Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

doi: 10.3389/fbioe.2020.00198

Figure Lengend Snippet: Collagen orientation calculation on SHG images of human pancreatic tissue with CurveAlign (CA) and its comparison with manual measurement and two other open-source tools including structure tenor based OrientationJ (OJ) and Fourier transform-based CytoSpectre (CS). (A–D) show the original SHG images and the location of eight ROIs. (E–H) show the manually labeled fibers (in magenta) overlaid on the original images of ROIs 1, 3, 5, and 7, respectively. (I–L) show curvelets (in green color) represented orientations on the original images of ROIs 1, 3, 5 and 7, respectively. The bottom row shows the comparison in orientation (left) and alignment (right). For the ROIs with relative larger alignment coefficient including ROIs 3–8, all the methods yield similar orientation. For ROIs 1–2 with relative small alignment, the discrepancy becomes bigger, with the CurveAlign Curvelets analysis mode (CA-CT) being closest to the manual measurement. All the methods share some similar trends in alignment measurement, with the CurveAlign fiber segments analysis mode (CA-CTF) being closest to the manual measurement. The differences are mainly due to the different fiber orientation detection algorithm and fiber alignment definition. Images (A–D) are shown at the same scale while images (E–L) are shown at the same scale. Scale bar equals 50 microns.

Article Snippet: Moreover, we have developed a prototype of KNIME ( ) nodes for CurveAlign and CT-FIRE for a convenient feature statistical analysis, classification, and visualization.

Techniques: Comparison, Labeling

Journal: Frontiers in Bioengineering and Biotechnology

Article Title: Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

doi: 10.3389/fbioe.2020.00198

Figure Lengend Snippet: An example of using CurveAlign to create tumor boundary from a bright-field image and quantify the relative angle on a breast cancer TMA core. (A) The SHG image, (B) Original bright-field image, (C) SHG image (in yellow) overlaid on top of the registered bright-field image. (D) Segmentation generated boundary mask. (E) Heatmap of the relative angle with red color shows the region where one or more fibers have an angle larger than 60°. (F) CurveAlign overlay image with the lines indicating the fiber center locations and orientations overlaid on the top of the SHG image; the outline of the tumor boundary is highlighted in yellow, and the two rectangular ROIs are in magenta; a blue line is used to associate the center of fiber with the corresponding boundary locations, and the red lines indicate the fibers located either beyond the distance range or inside the boundary, and green lines are the fibers of interest. (G) and (H) Zoomed-in ROI results. The arrows in these images show that the fibers either more parallelly aligned in (G) with respect to the boundary or are more perpendicularly aligned in (H) with respect to the tumor boundary. In boundary creation, pixel per micron ratio was set to 1.65; fiber extraction in CT-FIRE used default settings; the distance parameter was set to 150 pixels; the SHG image size is 2048 by 2048 pixels, and the sizes of ROI are identically set to 256 by 256 pixels. Images (A,C–F) are shown at the same scale while images (G) and (H) are shown at the same scale. Scale bar equals 100 microns.

Article Snippet: Moreover, we have developed a prototype of KNIME ( ) nodes for CurveAlign and CT-FIRE for a convenient feature statistical analysis, classification, and visualization.

Techniques: Generated, Extraction

Journal: Frontiers in Bioengineering and Biotechnology

Article Title: Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods

doi: 10.3389/fbioe.2020.00198

Figure Lengend Snippet: Validation of individual fiber tracking and orientation detection. (A) shows the 30 straight fibers with given fiber properties. (B) CT-FIRE individual fiber overlay image of (A) . (C) CurveAlign CT-curvelets overlay image of (A) . (E) shows the 30 curvy fibers with given fiber properties. (F) CT-FIRE individual fiber overlay image of (E) ; CurveAlign CT-curvelets overlay image of (A) . Both CT-FIRE fibers [color lines in (B) and (F) ] and curvelets [green lines with red center point in (C) and (G) ] are mostly faithfully overlaid on the actual fiber directions. The box plots of average orientation and alignment of the 100 synthetic images in each dataset are shown in (D) and (H) , respectively. The box plots (D) and (H) of the 100 synthetic images in each dataset show that the calculated orientations and alignment are close to the setting parameters. In the boxplot, the red line represents the median; the blue lines represent the 25th and 75th percentiles, respectively; the dashed lines and black lines indicate the lower and upper limits of the data points that are not considered as outliers; and the red crosses represent outliers. The t test shows that all the analysis modes yield the same mean values as the control values for both orientation and alignment at the 5% significance level except for the alignment calculated under the CT mode. CTF-S, CT-FIRE individual fiber mode for straight fiber images; CT-S, CT-curvelets mode for straight fiber images; CTF-C, CT-FIRE individual fiber mode for curvy fiber images; CT-C, CT-curvelets mode for curvy fiber images.

Article Snippet: Moreover, we have developed a prototype of KNIME ( ) nodes for CurveAlign and CT-FIRE for a convenient feature statistical analysis, classification, and visualization.

Techniques: Biomarker Discovery, Control

Journal: Nature Communications

Article Title: The serine proteases dipeptidyl-peptidase 4 and urokinase are key molecules in human and mouse scar formation

doi: 10.1038/s41467-021-26495-2

Figure Lengend Snippet: A Picrosirius red staining and immunofluorescent staining of B Col3a1 and C fibronectin in mouse skin and scars are shown. Four mice per group were analyzed. Arrows indicate areas of increased matrix density. D H&E images of mouse skin and scars. Squares indicate areas analyzed for collagen alignment. Histograms illustrate measurement of fiber orientation. E Calculation of alignment coefficient by CurveAlign in mouse skin and scar. N = 4 mice were analyzed per group, and three to four Regions of interest were calculated per image. Whiskers represent range maximum and minimum values with <1.5 interquartile range, boxes represent 25th–75th quartiles, line represents mean. Statistical significance was tested using one-way ANOVA with Tukey post-test. Skin vs Scar untreated p < 0.0001; Scar untreated vs Scar+BC-11 p = 0.0018; Scar untreated vs Scar+Sitagliptin p = 0.551. This mouse experiment was performed once, repetition of the experiment was not permitted by the ethics committee. NS p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001. Source data are provided as a Source data file.

Article Snippet: Collagen bundle alignment has been calculated using Curvealign V4.0 Beta, a curvelet transform-based, open-source MATLAB software.

Techniques: Staining

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: An example of using CT-FIRE mode without the boundary mode of CurveAlign for both full image and ROI analyses in pancreatic tissue. The top row shows the SHG image from different types of pancreatic tissue. The middle row shows the CT-FIRE extracted fibers highlighted by different colored lines for the purpose of contrast, which are overlaid upon the SHG image. The bottom row is the “Overlay” image generated by CurveAlign showing the location (red dots) and orientation (green lines) of the extracted fibers as well as the annotated ROI overlaid upon the SHG image. The quantification of the full image and the representative ROI are displayed in the format of “mean orientation/alignment” at the top left corner of the middle row and bottom row, respectively. Both full image-based and ROI-based quantifications show that collagen fibers are more aligned in malignant ducts (Grade 1–3) than in normal and benign ducts. Default parameters were used here. Image size is 1024 × 1024 pixels, and ROI size is 256 × 256 pixels. The scale bar at the top left column indicates 50 μm, and all images are shown at the same scale

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques: Generated

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: An example of using CurveAlign to quantify relative angle and ROI-based alignment on breast cancer tissue microarray. The first column shows the SHG image (in yellow) overlaid on the bright-field H&E image with four rectangular ROI annotations (in yellow) (top), the orientations and locations of extracted fibers using CT-FIRE mode (in green color) with four ROI annotations (in magenta) overlaid on the SHG image (in gray) (middle), and four rectangular ROI annotations (in yellow) overlaid on the SHG image (in gray) (bottom), respectively. The remaining four columns from left to right show the cropped images of the four ROIs, where for the ones in the top row, ROI name as well as its mean relative angle and ROI-based alignment in the format of “ROI name: mean relative angle/ROI alignment.” In the middle row, the blue line is used to associate the center of fiber extracted by CT-FIRE with the corresponding boundary locations, and the red line shows the fibers located either beyond the distance range or within the boundary. In the bottom row, the locations and orientations of fiber segments analyzed by CFR mode were indicated by red dots and green lines. From the figure, we can see that fibers in ROI 1 and ROI 3 are both well aligned, but there are more fibers in ROI 3 that are more perpendicularly aligned with respect to the tumor boundary. The boundary creation parameter is the same as in Fig. 6, i.e., pixel per micron ratio was set to 2; fiber extraction in CT-FIRE used default settings; the distance parameter was set to 250 pixels; the fraction of kept curvelets is set to 0.06. The image size is 2048 × 2048 pixels, and the sizes of ROI are identically set to 128 × 128 pixels. The scale bar for the full size image at the first column of the first row indicates 100 μm, scale bar for the ROI image at the second column of the first row indicates 25 μm, and all images either full size images or ROIs are shown at the same scale

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques: Microarray, Extraction

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: Schematic workflow of quantifying collagen alignment using CurveAlign for a single image. For the images in step 4, the fiber location and orientation were highlighted by red dots and green lines, respectively; the red lines indicate the fibers are out of the interested region. For [4B], there are two types of ROI analysis, type 1 ([4Ba]) can directly run CFR mode on the annotated ROI, but type 2 [4Bb] needs to run a full image analysis first either in CFR mode or in CT-FIRE mode. CTF, CT-FIRE; CFR, curvelets fiber representation; BD, with boundary; no BD, without boundary; FULL, full image analysis; and ROI, ROI analysis. The scale bar shown in the image at the top middle column indicates 50 μm, and all images are shown at the same scale

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques:

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: Graphical user interface of CurveAlign (a) and CT-FIRE (b)

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques:

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: Two fiber analysis modes in CurveAlign: (a) representative curvelets used in CFR mode; (b) extracted individual fibers used in CT-FIRE. This image of a relatively low-resolution portion of a breast tissue microarray illustrates the ability of the CurveAlign platform to extract fibers even when the fibers are relatively low signal to noise ratio but also demonstrates the difference between the two modes in fiber extraction. In (a), the red dots show the fiber location and green lines show the orientation. In (b), extracted fibers are displayed in different colored lines. CFR mode (a) indicates the most prominent fibers but does not provide individual fiber extraction as in CT-FIRE mode (b), which instead provides the information for entire fibers. CFR mode missed some fibers in the region annotated in red ellipse in (a) where fibers have relative lower intensity values. For the fiber analysis here, all parameters were kept as default ones except that, in CFR mode, the fraction of kept curvelet was set to 0.06. The image size is 512 pixels x 512 pixels. The scale bar at the upper left corner of (a) indicates 50 μm, and all images are shown at the same scale

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques: Microarray, Extraction

Journal: Methods in molecular biology (Clifton, N.J.)

Article Title: Methods for Quantifying Fibrillar Collagen Alignment

doi: 10.1007/978-1-4939-7113-8_28

Figure Lengend Snippet: Demonstration of typical outputs of CurveAlign: (1) The top row shows the relative angle (with respect to a boundary) using fibers extracted in CT-FIRE mode, the left column of this row shows that the blue line is used to associate the center of the fiber extracted by CT-FIRE with the corresponding boundary location, and the red line is used to show the fibers located either beyond the distance range or within the boundary; the heatmap at the middle column uses red color to indicate larger relative angles, and the histogram at the right column shows the distribution of the relative angle of fibers within the range of 0 to 90°; (2) the middle row shows the angle (with respect to the horizontal) measurement with CFR mode, and the left column of this row uses a red dot to indicate the center of fiber segments and a green line to indicate the fiber orientation at that point; the heatmap at the middle column uses red color to indicate well aligned fiber regions, and the histogram at the right column shows the distribution of the angles within the range of 0 to 180°; and (3) the bottom row shows ROI analysis based on the result from the CFR results shown in the middle row. Two magenta rectangular ROIs are annotated on the SHG image at the first column of this row, the histograms of angles within these two ROIs are displayed at the middle and right columns. Both the mean angle and alignment coefficient are listed below each histogram except that alignment is not calculated based on the relative angle data. The boundaries were cropped from the mask image shown in Fig. 6; fiber extraction in CT-FIRE used default settings; the distance parameter was set to 250 pixels; the fraction of kept curvelets is set to 0.06, the image size is 512 × 512 pixels, and the sizes of ROI are identically set to 128 × 128 pixels. The scale bar at the upper left corner of the top row indicates 50 μm, and all images are shown at the same scale

Article Snippet: Download the MATLAB Runtime Compiler (MCR) and the CurveAlign software from [ 36 ] and follow the detailed requirements and installation instructions from the above web page.

Techniques: Extraction