Matt Figdore

> Hi Matt @mfigdore , I'm testing `connected_threshold` in [adaptive_thresh.py](https://github.com/neurodata/brainlit/blob/develop/brainlit/algorithms/generate_fragments/adaptive_thresh.py) with a simple image as input: > `img = np.array([[[100, 250], [800, 300]], [[1200, 2000], [3000, 2500]]])` and a seed...

Running the code in the function manually with the `img` and `seed` you provided, it seems to work for me (although `seed` might need to be a list `[(1,0,1)]` --...

@FelixChihTing Does the tutorial work? Also, I suggest you check with others to see if it's a problem related to your OS or simpleITK version

> I believe it's an [issue of SimpleITK](https://github.com/SimpleITK/SimpleITK/issues/1098). @FelixChihTing Does the solution proposed of casting to 'int' fix it?

> @mfigdore currently only the following block in the [tutorial](https://github.com/neurodata/brainlit/blob/develop/docs/notebooks/algorithms/tutorial_notebook_adaptive_thresh.ipynb) is working: > > `from skimage.data import astronaut` > > `# create the viewer and display the image` > >...

@FelixChihTing Please see https://github.com/neurodata/brainlit/pull/226 which I believe will address the error.

@FelixChihTing Should be `labels = connected_threshold(img, [(1,0,1)] )`

@FelixChihTing Please refer to SimpleITK documentation. https://simpleitk.readthedocs.io/en/master/link_FastMarchingSegmentation_docs.html > A Gaussian with a parameterized sigma is used during the gradient computation to enable the level-set to slow down near edges. The...

> Hi @mfigdore, i'm updating the [adaptive thresh notebook](https://github.com/neurodata/brainlit/blob/CTalgCodCov/docs/notebooks/algorithms/adaptive_thresh_tutorial.ipynb), may I ask how do you put the seeds to each case to ensure desirable results? > In one case, I...

Try this: ``` event.preventDefault()} onEscapeKeyDown={event => event.preventDefault()} > ```