Average precision of top ranked results for different methods after ninth feedback.

<p>Average precision of top ranked results for different methods after ninth feedback.</p

AP of DFISOMAP, LPP, BDA, ELPP, LLE, LDA, ISOMAP and CSVM.

<p>Subfigures (A), (B), (C), (D) and (E) detail AP in the top 10, 20, 30, 40, and 50 results, respectively.</p

Visually similar medical images contain different semantic meanings.

<p>The chest radiographs shown in this figure have a similar visual appearance but belong to different semantic categories. Images are taken from IRMA medical image dataset.</p

Examples of query image.

<p>Examples of query image.</p

A_Z values of MLLE with different distance metrics on different IRMA category.

<p>A_Z values of MLLE with different distance metrics on different IRMA category.</p

Comparison of sensitivity, specificity and DOR for MLLE, LLE, MSE, LE and PCA on IRMA category 1.

<p>Comparison of sensitivity, specificity and DOR for MLLE, LLE, MSE, LE and PCA on IRMA category 1.</p

Example images from IRMA medical image data set. Each image belongs to a different category.

<p>Example images from IRMA medical image data set. Each image belongs to a different category.</p

Average recall of DFISOMAP with differentin top50 results, andincreases from 0 to 100, with step 10.

<p>Average recall of DFISOMAP with differentin top50 results, andincreases from 0 to 100, with step 10.</p

Query and top ten retrieved medical images.

<p>(A) Query image. (B) Retrieval results of MLLE. (C) Retrieval results of LLE. (D) Retrieval results of PCA. (E) Retrieval results of LE. (F) Retrieval results of MSE.</p

Comparison of ROC curves for MLLE, LLE, MSE, LE and PCA on different IRMA category. The classifier is KNN.

<p>(A) ROC curves obtained on IRMA category 14. (B) ROC curves obtained on IRMA category 16. (C) ROC curves obtained on IRMA category 20. (D) ROC curves obtained on IRMA category 21. (E) ROC curves obtained on IRMA category 22. (F) ROC curves obtained on IRMA category 49.</p