I have a set of images representing the mean curvature of a human back surface.

What I want to do is to "scan" the image for points which have similar, reflected "counterparts" in some other part of the image (most likely symmetrical to the midline, but not necessarily since there might be deformities). Some image-stitching techniques use this to "auto-detect" similar points between images, but I want to detect them for both sides of the same image.

The ultimate goal is to find a continuous, most probably curved, longitudinal line that adaptively divides the back in symmetric "halves".

A sample image is placed below. Notice that not all the regions are symmetrical (specifically, just above the center of the image, the red vertical "strip" deviates to the right). That region should receive a bad score, or whatever, but then the local symmetry would be defined from symmetrical points placed farther away. In any case, I'll have to adapt any algorythm to my application domain, but what I'm after is som correlation/convolution/pattern-matching strategy, there must already be something around, I think.

(EDIT: there are more images below, and some more explanation)

![enter image description here](https://i.stack.imgur.com/jf709.jpg)

EDIT: as requested, I'll include more typical images, either well-behaved and problematic. But instead of colormapped images, they are grayscale ones, so that color relates directly to data magnitude, which didn't happened with the colored image (provided just for communication). Although the gray images seem to lack contrast compared to the colored one, the data gradients are there and can be brought up with some adaptive contrast if desired.

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1) Image of a very symmetrical subject:

![enter image description here](https://i.stack.imgur.com/h4L4J.jpg)

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2) Image of the same subject at a different moment. Although there are more "features" (more gradients), it doesn't "feel" so symmetric as before:

![enter image description here](https://i.stack.imgur.com/s3VX7.jpg)

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3) A thin young subject, with convexities (bony protrusions, denoted by lighter regions) at the midline instead of the more common concave midline:

![enter image description here](https://i.stack.imgur.com/wqqYj.jpg)

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4) A young person with spinal deviation confirmed by X-Ray (note the asymmetries):

![enter image description here](https://i.stack.imgur.com/LltP7.jpg)

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5) The typical "tilted" subject (although mostly symmetrical around the curved midline, and as such not properly "deformed"):

![enter image description here](https://i.stack.imgur.com/n4lrr.jpg)

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Any help is much welcome!