diff --git a/Utilities/ITK/Code/BasicFilters/itkBinaryThresholdImageFilter.h b/Utilities/ITK/Code/BasicFilters/itkBinaryThresholdImageFilter.h
index 19e21bff4d919ad27e52294d7e3c597fb9769d6d..40dc75874c1fa8f327c8b4d5c80cf4c252d2030e 100644
--- a/Utilities/ITK/Code/BasicFilters/itkBinaryThresholdImageFilter.h
+++ b/Utilities/ITK/Code/BasicFilters/itkBinaryThresholdImageFilter.h
@@ -37,7 +37,7 @@ namespace itk
  * More precisely
  * \f[ Output(x_i) =
        \begin{cases}
-         InsideValue & \text{if $LowerThreshold \leq x_i \leq UpperThreshold$} \     \
+         InsideValue & \text{if $LowerThreshold \leq x_i \leq UpperThreshold$} \\
          OutsideValue & \text{otherwise}
        \end{cases}
    \f]
diff --git a/Utilities/ITK/Code/BasicFilters/itkContourDirectedMeanDistanceImageFilter.h b/Utilities/ITK/Code/BasicFilters/itkContourDirectedMeanDistanceImageFilter.h
index 27fbbe506748a456abfba1fece6b36e4d61f0e72..d71f006b42e48ac062810331de9f653312e56730 100644
--- a/Utilities/ITK/Code/BasicFilters/itkContourDirectedMeanDistanceImageFilter.h
+++ b/Utilities/ITK/Code/BasicFilters/itkContourDirectedMeanDistanceImageFilter.h
@@ -30,7 +30,7 @@ namespace itk {
  *
  * ContourDirectedMeanDistanceImageFilter computes the distance between the set
  * non-zero pixels of two images using the following formula:
- * \f[ h(A,B) = \mean_{a \in A} \min_{b \in B} \| a - b\| \f]
+ * \f[ h(A,B) = mean_{a \in A} \min_{b \in B} \| a - b\| \f]
  * where \f$A\f$ and \f$B\f$ are respectively the set of non-zero pixels
  * in the first and second input images. It identifies the point \f$ a \in A \f$
  * that is farthest from any point of \f$B\f$ and measures the distance from \f$a\f$
diff --git a/Utilities/ITK/Code/BasicFilters/itkSigmoidImageFilter.h b/Utilities/ITK/Code/BasicFilters/itkSigmoidImageFilter.h
index 94da66b6610cf491a8c924adbaf47fbf658975b7..035e274913205d2a9d56ad19b65930264a84a153 100644
--- a/Utilities/ITK/Code/BasicFilters/itkSigmoidImageFilter.h
+++ b/Utilities/ITK/Code/BasicFilters/itkSigmoidImageFilter.h
@@ -29,7 +29,7 @@ namespace itk
  * the sigmoid fuction. The resulting total transfrom is given by
  *
  * \f[
- * f(x) = (Max-Min) \cdot \frac{1}{\left(1+e^{-(\frac{ x - \beta }{\alpha}\right)}} + Min
+ * f(x) = (Max-Min) \cdot \frac{1}  {\left( 1+e^{-\frac{ x - \beta }{\alpha}}  \right)} + Min
  * \f]
  *
  * Every output pixel is equal to f(x). Where x is the intensity of the
diff --git a/Utilities/ITK/Code/Common/itkKLMSegmentationRegion.h b/Utilities/ITK/Code/Common/itkKLMSegmentationRegion.h
index 8af11f5e7207dd320aa53af4fa1a4a0e8f632af3..0ab1315b5aa10fd02c7f52f77099cdee137a796d 100644
--- a/Utilities/ITK/Code/Common/itkKLMSegmentationRegion.h
+++ b/Utilities/ITK/Code/Common/itkKLMSegmentationRegion.h
@@ -67,7 +67,7 @@ namespace itk
  *  \end{tabular}\f]
  *
  * Region borders are shown as ``E''.
- * \f[\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|}
+ * \f[\begin{tabular}{|c|c|c|c|c|c|c|c|c|c|c|}
  * \hline
  *   C & C & C &   & C & C & C &   & C & C & C \\ \hline
  *   C & C & C & E & C & C & C & E & C & C & C \\ \hline
diff --git a/Utilities/ITK/Code/Numerics/Statistics/itkLogLikelihoodGoodnessOfFitFunction.h b/Utilities/ITK/Code/Numerics/Statistics/itkLogLikelihoodGoodnessOfFitFunction.h
index f05a862eaa5287a5a5c84e959f2f467aabb20eb5..ed078e9a8a3723699eb8ce02803138674a918ad6 100644
--- a/Utilities/ITK/Code/Numerics/Statistics/itkLogLikelihoodGoodnessOfFitFunction.h
+++ b/Utilities/ITK/Code/Numerics/Statistics/itkLogLikelihoodGoodnessOfFitFunction.h
@@ -31,7 +31,7 @@ namespace Statistics{
  * The statistics is
  *    \f$ \sum^{k}_{i=1}x_{i}\log(x_{i}/n\pi_{0i}\f$
  *  
- *  where \f$ x_{i] \f$ is the observed frequency of the \f$i\f$th bin, and
+ *  where \f$ x_{i} \f$ is the observed frequency of the \f$i\f$th bin, and
  * \f$n\pi_{0i}\f$ is the expected frequency.
  * 
  *