Hi.
I loaded radial dicom images from MRI and, I can´t see the whole volume. Just appears one image at a time and on the other anatomical planes the black screen and the bar.
Or occurs this:
Someone can help me?
Thank you
Hi.
I loaded radial dicom images from MRI and, I can´t see the whole volume. Just appears one image at a time and on the other anatomical planes the black screen and the bar.
Or occurs this:
Someone can help me?
Thank you
The slice view shows the intersection of the slice plane and the selected image. Since the acquired image is only a single slice, the intersection is just a line. You can make the slice view dynamically follow the image by using Volume Reslice Driver module in SlicerIGT extension.
Slicer can also reconstruct the rotational acquisition to a 3D volume or 4D volume sequence using the “Reconstruct 4D cine-MRI” module in SlicerHeart extension.
Thank you so much for your help.
I tried that, but appear this error and then the images are blurry and I cant segment it. Because I cant distinguish the cartilage of hip, due to bad quality of images when submited of this process .
I need segment the radial images of hip.
You can increase the resolution of the output image by setting a smaller spacing value.
How do you envision to use the images if not reconstructing a Cartesian volume from them? What is the overall goal of your What is the overall goal of your project?
This is the cartesian volume that are you talking about?
My goal is to reconstruct the human hip in 3D using radial MRI images. Later, I also need to reconstruct the hip joint articular cartilage.
The doctor said that the best images to segment are the radials.
I thought to go to the semgment editor and segment the images obtained through the" Reconstruct 4D cine-MRI".
thank you for your kindness
Yes, it is the volume reconstructed to have parallel slices.
Without having a Cartesian volume, you can only do very limited measurements or processing, as you can only process each 2D slice separately. For example, you can measure local features (thickness, diameter, cross-sectional area) or define contours that may be used for reconstructing very thin structures.
For reconstructing 3D shapes, measuring volumes, 3D surface areas, etc. a Cartesian volume representation (this is what “Reconstruct 4D cine-MRI” module creates) is generally more suitable.
But… Why the volume is not clear? I can´t see the bone.
I don´t want the radial images reconstructed on the axial, sagital and coronal planes. I want segment radial images.
I tried the Volume Reslice Driver that you indicated, and then I went to the segment editor (using grow from seeds) , to segment only radial images but it´s not possible. I don´t know why… How can I do?
I can only paint the rectangular slice that appears in the image. It´s not possible paint the other parts of the bone.
You can set as high output resolution as you need.
It would be awesome if high-resolution arbitrarily oriented slices could be used for creating high-resolution 3D segmentations. However, the issue is that between your high-resolution slices there are huge gaps where you don’t know anything about the bone shape. How do you want do deal with this?
I would recommend to build a 3D Cartesian volume and segment that. Nice and simple. You can choose any resolution that your computer can handle.
You can choose to segment each slice. For this, you need to create a segmentation sequence (add a segmentation node under the same sequence browser node of your image sequence). But this would just give you a set of disconnected binary labelmaps. What would you do with such a series of single-slice binary labelmaps?
You could also “segment” a structure by adding a closed curve node at each slice (then you don’t need to set up a new a sequence, you could just add a new node for each slice). However, the problem remains: what do you do with those closed contours?
We need more information about your overall goal - what is the clinical problem you want to address and how, and then we can give further advice on how to achieve that.