STYLE: Improve style across miscellaneous episode files

_episodes/introduction.md

@@ -39,10 +39,9 @@ brain tissue. DWI has been used extensively to diagnose stroke, assess white
 matter damage in many different kinds of diseases, provide insights into the 
 white matter connectivity, and much more!
 
-![fiber_configurations]
-({{ relative_root_path }}/fig/introduction/diffusion_direction_new.png) 
-\Diffusion along X, Y, and Z directions. The signal in the left/right oriented 
-corpus callosum is lowest when measured along X, while the signal in the 
++![Diffusion along different directions]({{ relative_root_path }}/fig/introduction/diffusion_directions.png) \
+\Diffusion along X, Y, and Z directions. The signal in the left/right oriented
+corpus callosum is lowest when measured along X, while the signal in the
 inferior/superior oriented corticospinal tract is lowest when measured along Z.
 
 ## b-values & b-vectors
@@ -71,8 +70,7 @@ properties. The DWI acquisition process is thus:
 For the rest of this lesson, we will make use of a subset of a publicly
 available dataset, ds000221, originally hosted at [openneuro.org](https://openneuro.org/datasets/ds000221/versions/1.0.0).
 The dataset is structured according to the Brain Imaging Data Structure
-([BIDS](https://bids-specification.readthedocs.io/en/etable/)). Please check
-the [the BIDS-dMRI Setup page](https://carpentries-incubator.github.io/SDC-BIDS-dMRI/setup.html)
+([BIDS](https://bids-specification.readthedocs.io/en/etable/)). Please check the [BIDS-dMRI Setup page](https://carpentries-incubator.github.io/SDC-BIDS-dMRI/setup.html)
 to download the dataset.
 
 Below is a tree diagram showing the folder structure of a single MR subject and

_episodes/preprocessing.md

@@ -52,9 +52,9 @@ lesson.
 ### Brainmasking
 
 The first step to the preprocessing workflow is to create an appropriate
-brainmask from the diffusion data! Start by first importing the necessary modules and 
-reading the diffusion data along with the coordinate system (the affine)! We will also grab 
-the anatomical T1w image to use later on, as well as the second inversion from the anatomical 
+brainmask from the diffusion data! Start by first importing the necessary modules and
+reading the diffusion data along with the coordinate system (the affine)! We will also grab
+the anatomical T1w image to use later on, as well as the second inversion from the anatomical
 acquisition for brainmasking purposes.
 
 ~~~
@@ -128,7 +128,7 @@ differs. Typically, this is done using two acquisitions acquired with opposite
 phase-encoding directions, which results in the same field creating distortions
 in opposing directions.
 
-![blips]({{ relative_root_path }}/fig/preprocessing/blip_up_blip_down.png)
+![Blip up and blip down pairs]({{ relative_root_path }}/fig/preprocessing/blip_up_blip_down.png) \
 Opposite phase-encodings from two DWI
 
 Here, we will make use of the two opposite phase-encoded acquisitions found in

code/introduction.ipynb

@@ -28,7 +28,7 @@
     "diagnose stroke, assess white matter damage in many different kinds of diseases, \n",
     "provide insights into the white matter connectivity, and much more!\n",
     "\n",
-    "![fiber_configurations](../fig/introduction/diffusion_direction_new.png) \\\n",
+    "![[Diffusion along different directions](../fig/introduction/diffusion_directions.png) \\\n",
     "Diffusion along X, Y, and Z directions. The signal in the left/right oriented \n",
     "corpus callosum is lowest when measured along X, while the signal in the \n",
     "inferior/superior oriented corticospinal tract is lowest when measured along Z."

code/preprocessing.ipynb

@@ -150,7 +150,7 @@
     "phase-encoding directions, which results in the same field creating distortions\n",
     "in opposing directions.\n",
     "\n",
-    "![blips](../fig/preprocessing/blip_up_blip_down.png)\\\n",
+    "![Blip up and blip down pairs](../fig/preprocessing/blip_up_blip_down.png)\\\n",
     "Opposite phase-encodings from two DWI\n",
     "\n",
     "Here, we will make use of the two opposite phase-encoded acquisitions found in\n",