Figure 4
From: A robust nonlinear tissue-component discrimination method for computational pathology
Evaluation of nonlinear tissue-component discrimination (NLTD) method. (a–c) Nuclei intensity comparison between NLTD and color deconvolution (CD) approaches. Representative nuclei from several tissue types are shown, along with the NLTD and CD nuclei transformations. The intensity of each color space is integrates along the dotted lines shown, with the NLTD intensity shown in purple and the CD intensity in brown. Intensity values are normalized linearly between 0 and 1, with 0 corresponding to the minimum value in the input image, and 1 corresponding to the maximum. (d) Typical breast cancer image.33 (e) Example of segmentation results from Otsu thresholding of the nuclei NLTD color space. Detected nuclei are overlaid on top of the image from panel (d). True positives are represented by a green dot, false positives by a red dot, and false negatives by a yellow dot. (f) Precision, (g) sensitivity, and (h) F-score values for segmentation results from 35 images. (i) Receiver-operating characteristic curve for change in segmentation parameterization (threshold value) for nuclei detection. Recall (sensitivity) is shown on the x axis, with precision shown on the y axis. Results from NLTD method are shown in black, with CD shown in gray.
