Add k-space basics tutorial for MRI reconstruction

git push -u origin add-kspace-basics-tutorial
Adds an introductory notebook covering k-space fundamentals, Fourier
transform connection, aliasing from undersampling, and MONAI's
reconstruction transforms using the fastMRI knee single-coil dataset.
Also adds the missing Reconstruction section to the main README.

Signed-off-by: Vidya Sagar <[email protected]>

Author: ViSaReVe

README.md

@@ -386,4 +386,12 @@ Example shows the use cases of using MONAI to evaluate the performance of a gene
 
 #### [VISTA2D](./vista_2d)
 This tutorial demonstrates how to train a cell segmentation model using the [MONAI](https://monai.io/) framework and the [Segment Anything Model (SAM)](https://github.com/facebookresearch/segment-anything) on the [Cellpose dataset](https://www.cellpose.org/).
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+
+#### <ins>**Reconstruction**</ins>
+##### [K-Space Basics with fastMRI Knee Data](./reconstruction/MRI_reconstruction/tutorials/01_kspace_basics_fastmri_knee.ipynb)
+This tutorial introduces MRI reconstruction fundamentals: what k-space is, how the Fourier transform connects k-space to images, why undersampling causes aliasing, and how MONAI's reconstruction transforms process k-space data. Uses the fastMRI knee single-coil dataset.
+##### [U-Net MRI Reconstruction](./reconstruction/MRI_reconstruction/unet_demo)
+Training and inference for accelerated MRI reconstruction using BasicUNet on the fastMRI brain multi-coil dataset.
+##### [VarNet MRI Reconstruction](./reconstruction/MRI_reconstruction/varnet_demo)
+Training and inference for accelerated MRI reconstruction using e2e-VarNet on the fastMRI brain multi-coil dataset.
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