Why is K-Means considered a special case of Expectation-Maximization?

K-Means is equivalent to EM for Gaussian mixtures with equal variance and hard assignments.

In EM, soft assignments are used to estimate Gaussian mixture parameters. K-Means simplifies this by assuming identical isotropic covariance and assigning each point to the nearest centroid deterministically (hard EM).