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Binary image segmentation using Fast Marching Method

`BW = imsegfmm(W,mask,thresh)`

`BW = imsegfmm(W,C,R,thresh)`

`BW = imsegfmm(W,C,R,P,thresh)`

```
[BW,D] =
imsegfmm(___)
```

`[`

returns the normalized geodesic
distance map `BW`

,`D`

] =
imsegfmm(___)`D`

computed using the Fast Marching
Method. `BW`

is a thresholded version of `D`

,
where all the pixels that have normalized geodesic distance values
less than `thresh`

are considered foreground pixels
and set to `true`

. `D`

can be
thresholded at different levels to obtain different segmentation results.

`imsegfmm`

uses double-precision floating point operations for internal computations for all classes except class`single`

. If`W`

is of class`single`

,`imsegfmm`

uses single-precision floating point operations internally.`imsegfmm`

sets pixels with`0`

or`NaN`

weight values to`Inf`

in the geodesic distance image`D`

. These pixels are part of the background (logical false) in the segmented image`BW`

.

[1] Sethian, J. A. *Level Set Methods and Fast
Marching Methods: Evolving Interfaces in Computational Geometry, Fluid
Mechanics, Computer Vision, and Materials Science*, Cambridge
University Press, 2nd Edition, 1999.

Image Segmenter | `activecontour`

| `gradientweight`

| `graydiffweight`

| `graydist`

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