udpdated Unet

src/14.example_fastMRI_Unet.ipynb

@@ -26,12 +26,10 @@
     "repository, which is a collaborative research project aimed at advancing\n",
     "the field of medical imaging using machine learning techniques.\n",
     "\n",
-    ".. math::\n",
+    "$$\\mathbf{\\hat{x}} = \\mathrm{arg} \\min_{\\mathbf{x}} || \\mathcal{U}_\\mathbf{\\theta}(\\mathbf{y}) - \\mathbf{x} ||_2^2$$\n",
     "\n",
-    "    \\mathbf{\\hat{x}} = \\mathrm{arg} \\min_{\\mathbf{x}} || \\mathcal{U}_\\mathbf{\\theta}(\\mathbf{y}) - \\mathbf{x} ||_2^2\n",
-    "\n",
-    "where :math:`\\mathbf{\\hat{x}}` is the reconstructed MRI image, :math:`\\mathbf{x}` is the ground truth image,\n",
-    ":math:`\\mathbf{y}` is the input MRI image (e.g., k-space data), and :math:`\\mathcal{U}_\\mathbf{\\theta}` is the U-Net model parameterized by :math:`\\theta`.\n",
+    "where $\\mathbf{\\hat{x}}$ is the reconstructed MRI image, $\\mathbf{x}$ is the ground truth image,\n",
+    "$\\mathbf{y}$ is the input MRI image (e.g., k-space data), and $\\mathcal{U}_\\mathbf{\\theta}$ is the U-Net model parameterized by $\\theta$.\n",
     "\n",
     ".. warning::\n",
     "    We train on a single image here. In practice, this should be done on a database like fastMRI [fastmri]_.\n",