[Announcements] release of Landmarker 1.3 and ROIEditor 1.3

[support at mristudio.org]

Dear Mristudio users,

We have released Landmarker 1.3 and ROIEditor 1.3. Please go to our website to
download them.

The new features are as follows:

Landmarker 1.3

1. ROI-based manual intensity matching

Before LDDMM, intensity profiles need to be adjusted between the template and
the subject if non-quantitative images (such as b0 and T2-weighted images) are
used. Currently there are manual and automated histogram matching functions are
available in Landmarker. There is also an option for remote automated histogram
matching when the images are sent to our server. However, because you can not
check the quality of the matching, we recommend to use the matching functions in
Landmarker.

The new manual intensity matching is based on intensities inside the ROI. In
this approach, users are asked to define corresponding regions between the
template (atlas) and the subject data. High intensity (e.g. CSF), medium
intensity, and low intensity regions should be specified to capture the entire
intensity range both in the atlas and the subject. Then the intensity profiles
are matched between the two.

This type of matching is necessary because image intensity of non-quantitative
images is arbitrary and there could be a large difference between the template
and the subject, which confuses LDDMM. This is, in theory, not necessary when
quantitative maps are used such as FA and Trace.

2. All the loaded images can be resampled at one time.

When image resampling functions are used (buttons in the "image" section), they
were applied only to the active images. Now, there is an option to apply them to
all loaded images.

3. These is a manual scaling when the data format of an image is changed to byte.

Before LDDMM, all image formats have to be converted to the byte format. This
can be done by the "BFW" button in the "image" section. In the older version,
this conversion was automatically done by taking the maximum intensity = 255.
With the new version, you can manually specify the conversion to the 0-255
range. When quantitative maps such as FA and Trace are converted to byte for
LDDMM, absolute scale should be used to achieve the optimum intensity matching.

4. Invert an AIR linear matrix when a xx.air file is provided.

Using Landmarker, we can do "inverse" transformation, in which our atlases are
transformed to each subject data. LDDMM provides K-map (forward) and H-map
(reverse), but AIR provides only forward (Image.air). This function can invert
the AIR transformation.

5. Jacobian calculation of a LDDMM map.

A new function to calculate Jacobian from LDDMM results (K-map) was added. This
extract volume change information from a K-map in a pixel-by-pixel manner.

6. Disable tensor reorientation.

When transformation is applied to a tensor field, Landmarker performs
tensor-reorientation whenever rotation components are involved. However, in
certain circumstances, users may want to turn off this function. For example,
when we do B0-susceptibility distortion correction, we believe tensor should not
be re-oriented because the distortion is just pixel-mislocation, which is
different from cross-subject transformation.

ROIEditor 1.3

1. The data format of a ROI data file created by ROIEditor is changed to WORD.

In the old version, it was byte, which could hold only up to 256 ROIs. Now you
can delineate more than 36,000 ROIs!

2. Hide all ROIs and show all ROIs.

In the old version, the show/hide of ROIs had to be controlled for each ROI
individually. Using this new function, all ROIs can be shown/hid at once.

3. Calculate the RGB of color images.

RGB values of color maps can now be quantified for each ROI.

4. Double click a ROI and the corresponding ROI object box in the ROI object
list will be highlighted.

It was sometimes difficult which ROI in the image correspond which ROI in the
ROI list. Now, by clicking an ROI in the image, you can identify the ROI object
in the ROI list.

5. Users can decide if zero is treated as no data in statistical calculation.

When there are pixels with "0" intensity in ROI, sometimes you don't want to
include the pixels for statistics (e.g. masked out pixels). You can choose
whether you want to include such pixels or not.


If you have any questions about these two new softwares, please send your email
to Mristudio-users or support at mristudio.org.



Thanks!


Mristudio Support