Let (MQP) be a MIQP that consists in minimizing a quadratic function subject to linear constraints. Our approach to solve (MQP) is first to consider (MQP'), an equivalent MIQP that has a convex objective function, additional variables and constraints, and additionnal quadratic constraints. Then, we propose a new Branch and Bound based on the relaxation of the quadratic constraints to solve (MQP'). We perform experiments on pure-and mixed-integer instances of medium size, and show that their solution times are improved by our Branch and Bound in comparison with two existing approaches.