Merge pull request #228 from danieldeidda/spect_ex

[ci skip] making SPECT solution and exercise consistent
SyneRBI · May 16, 2024 · c5bb3dc · c5bb3dc
2 parents 4581d44 + 4d42abc
commit c5bb3dc
Show file tree

Hide file tree

Showing 4 changed files with 197 additions and 39 deletions.
diff --git a/notebooks/SPECT/SPECT_OSEM.ipynb b/notebooks/SPECT/SPECT_OSEM.ipynb
@@ -8,6 +8,21 @@
     "A notebook to demonstrate the setup and basic OSEM reconstruction of a 2-dimensional dummy image using SIRF's SPECT projector"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Authors: Daniel Deidda and Sam Porter  \n",
+    "\n",
+    "CCP SyneRBI Synergistic Image Reconstruction Framework (SIRF).  \n",
+    "Copyright 2022 - 2024 National Physical Laboratory  \n",
+    "Copyright 2022 - 2024, 2021 University College London\n",
+    "\n",
+    "This is software developed for the Collaborative Computational Project in Synergistic Reconstruction for Biomedical Imaging (http://www.ccpsynerbi.ac.uk/).\n",
+    "\n",
+    "SPDX-License-Identifier: Apache-2.0"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -183,7 +198,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we need to create the acquisition model by first creating an acquisition matrix (SPECTUBMatrix) object and apply this to a sirf Acquisition Model (AcquisitionModelUsingMatrix) object"
+    "Now we need to create the acquisition model by first creating an acquisition matrix (SPECTUBMatrix) object, add attenuation, PSF, and apply this to a sirf Acquisition Model \n",
+    "(AcquisitionModelUsingMatrix) object. Hint (help(spect.SPECTUBMatrix))"
    ]
   },
   {
@@ -192,7 +208,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "### Acquisition Model code here ###"
+    "### Acquisition Model code here ###\n",
+    "# acq_model_matrix =?\n",
+    "help(spect.SPECTUBMatrix)"
    ]
   },
   {
@@ -239,12 +257,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "### Objective Function code here ###\n",
+    "# create objective function\n",
+    "obj_fun = spect.make_Poisson_loglikelihood(noisy_data)\n",
     "\n",
+    "### and now we apply a different resolution mdoel ### and\n",
+    "acq_model_matrix.set_resolution_model(0.1,0.1,full_3D=False)\n",
+    "acq_model_2 = spect.AcquisitionModelUsingMatrix(acq_model_matrix)\n",
+    "obj_fun.set_acquisition_model(acq_model_2)\n",
+    "\n",
+    "# create OSEM reconstructor object\n",
     "num_subsets = 21 # number of subsets for OSEM reconstruction\n",
     "num_subiters = 42 #number of subiterations (i.e two full iterations)\n",
-    "\n",
-    "### OSEM reconstructor code here ###"
+    "OSEM_reconstructor = spect.OSMAPOSLReconstructor()\n",
+    "OSEM_reconstructor.set_objective_function(obj_fun)\n",
+    "OSEM_reconstructor.set_num_subsets(num_subsets)\n",
+    "OSEM_reconstructor.set_num_subiterations(num_subiters)"
    ]
   },
   {
@@ -326,12 +353,15 @@
   },
   "language_info": {
    "codemirror_mode": {
-    "name": "ipython"
+    "name": "ipython",
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
-   "nbconvert_exporter": "python"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/SPECT/SPECT_OSEM_measured_data.ipynb b/notebooks/SPECT/SPECT_OSEM_measured_data.ipynb
@@ -165,12 +165,15 @@
   },
   "language_info": {
    "codemirror_mode": {
-    "name": "ipython"
+    "name": "ipython",
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
-   "nbconvert_exporter": "python"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/SPECT/SPECT_OSEM_measured_data_solution.ipynb b/notebooks/SPECT/SPECT_OSEM_measured_data_solution.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "962178b0",
+   "id": "0",
    "metadata": {},
    "source": [
     "Simple OSEM reconstruction demo for real data: \n",
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d91eaa49",
+   "id": "1",
    "metadata": {},
    "source": [
     "In this exercise you are going to apply what you learned in the previous notebooks about SPECT reconstruction to reconstruct real data. \n"
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f80fd2f7",
+   "id": "2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63,7 +63,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9e8458d6",
+   "id": "3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "08524093",
+   "id": "4",
    "metadata": {},
    "source": [
     "The following is not needed if the data is already downloaded"
@@ -84,7 +84,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bbca69aa",
+   "id": "5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -97,7 +97,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "931f651d",
+   "id": "6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -110,7 +110,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6ec9dcbc",
+   "id": "7",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "54ce83d9",
+   "id": "8",
    "metadata": {},
    "source": [
     "# Exercise 1: Simple Reconstruction:\n",
@@ -130,7 +130,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "58584f1f",
+   "id": "9",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -145,7 +145,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "850fd91f",
+   "id": "10",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -158,7 +158,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d14521ed",
+   "id": "11",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -173,7 +173,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "4479d023",
+   "id": "12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -188,7 +188,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0663ab88",
+   "id": "13",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -200,7 +200,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "82b2fcec",
+   "id": "14",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -216,7 +216,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "dd1042e3",
+   "id": "15",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -231,7 +231,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "51264d96",
+   "id": "16",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -244,7 +244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "57e0ffc1",
+   "id": "17",
    "metadata": {},
    "source": [
     "# Exercise 2: PSF Reconstruction:\n",
@@ -260,7 +260,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3f5fce65",
+   "id": "18",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -282,7 +282,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0c56f23b",
+   "id": "19",
    "metadata": {},
    "outputs": [],
    "source": [