A new approach to the automatic extraction of the lumen region and its boundary for gastrointestinal (GI) endoscopic images is presented. First, a quasi region of interest, the darker regions of the image, is segmented using a region splitting scheme termed progressive thresholding. The centre of mass of this segmented region acts as a seed for further processing. Then the lumen region is obtained using a region growing technique called the integrated neighbourhood search (INS). A new quad structure based technique is introduced to enhance the INS speed significantly. A back projection algorithm is suggested to optimise the search for pixels belonging to the lumen region and boundary. A boundary-thinning algorithm is also proposed to remove the redundant pixels from the lumen boundary and to generate a connected single pixel width boundary. The proposed approach does not need a priori knowledge about the image characteristics. The experimental results indicate that the proposed technique enhances the speed of conventional INS by 45.5% to 28.6% based on the lumen size varying from 22,709 pixels to 4947 pixels. The main advantage of the proposed technique is its high-speed response that facilitates real-time analysis of endoscopic images.