The performance of Simple Thresholding, Burget’s method, HLFs-RF and our method with boundary amending on the ISBI 2012 data set.

<p>The performance of Simple Thresholding, Burget’s method, HLFs-RF and our method with boundary amending on the ISBI 2012 data set.</p

Segmentation results for neuronal structures using the Kirsch operator.

<p>Segmentation results for neuronal structures using the Kirsch operator.</p

Thirty test EM images for segmentation from ISIB 2012.

<p>Thirty test EM images for segmentation from ISIB 2012.</p

Parameters used for reinforced gradient-descent curve shape fitting.

<p>We used a polynomial fitting function as the basis function: y = <i>θ_nxⁿ</i>+<i>θ_n</i>_-1<i>xⁿ</i>⁻¹+…+<i>θ</i>₀.</p

Segmentation results for neuronal structures using the Sobel operator.

<p>Segmentation results for neuronal structures using the Sobel operator.</p

Segmentation results for neuronal structures using the Roberts Cross operator.

<p>Segmentation results for neuronal structures using the Roberts Cross operator.</p

Pixel error, Rand error, and warping error for 30 EM images from ISBI 2012.

<p>In each column, the results on the left were obtained using our approach with amendment while those on the right were obtained using the approach without amendment.</p

Standard labeled results after neuronal structure segmentation provided by ISIB 2012.

<p>Standard labeled results after neuronal structure segmentation provided by ISIB 2012.</p

Macro averaging evaluation rating results for 30 test EM images from ISBI 2012 using the proposed approach with boundary amendment and the proposed approach without boundary amendment, as well as the Canny, Kirsch, LoG, Prewitt, Roberts Cross, and Sobel operators.

<p>Macro averaging evaluation rating results for 30 test EM images from ISBI 2012 using the proposed approach with boundary amendment and the proposed approach without boundary amendment, as well as the Canny, Kirsch, LoG, Prewitt, Roberts Cross, and Sobel operators.</p

The flow of the interactions in the reinforcement learning framework.

<p>The flow of the interactions in the reinforcement learning framework.</p