How can I obtain from a differential equation a stochastic version? Suppose $\frac{dx}{dt}=ax+b$ and then assume that $a=c+g$ where $g$ is a Wiener process. 

You should distinguish white noise and Brownian motion. Let $\xi_t$ be $\mathcal{N}(0,1)$ white noise, then if
$$
dy_t = \xi_t dt
$$
then $y_t\equiv$const (from the Law of Large Numbers).
In fact it's better to obtain ODE from SDE, vice versa can be done in the following way: you write perturbed equation
$$
dX_t = (aX_t + b)dt+\sigma(t,X_t)dB_t
$$
where $B_t$ is a Brownian motion ( = Wiener process). If you put $\sigma\equiv 0$ then 
$$
dx_t = (ax_t+b)dt
$$
Also, for arbitrary $\sigma$ it's true for the expected value of the perturbed system $m_t = \mathrm{E}[x_t]$ we have
$$
dm_t = (am_t+b)dt.
$$
You can choose any $\sigma$ you like - for example constant, linear in $X_t$, linear in time and so on. I suggest to put $\sigma$ independent of time to leave the system autonomous.
P.S. You can read in Oksendal that for the white noise $\xi_t$ it's not interesting to consider process with increments $\xi_t dt$ because of its triviality. In fact it's more "correct" to use agreement $dB_t = \xi_t\sqrt{dt}$.
