The invention relates to a medical lung MRI image segmentation method based on an adaptive contour model, and MRI equipment. The equipment comprises a main magnet system, a gradient magnetic field system, a radio frequency system and an operation and image processing system; the radio frequency system comprises a plurality of radio frequency coils which are respectively arranged in coil fixing devices, and different radio frequency receiving coils correspond to different detection parts on a patient. The method comprises the following steps: 1) preprocessing an input fused MRI image; 2) setting an initial contour line as c0 and setting the initial contour line as a circle according to the characteristics of the lung tumor image, and calculating an initial level set function phi 0 accordingto the c0; 3) updating a level set function phi n, and calculating c1 and c2 according to the current phi n; 4) checking whether iteration is convergent or not: if so, determining that c is the optimal contour line, and otherwise, continuing iteration; 5), after the target area is obtained, removing noise and some tiny protruding parts by using image morphological opening operation, smoothing theboundary, connecting the fracture part by using closed operation, and filling a cavity to obtain a target image. The method is high in segmentation precision and clear in edge, and is suitable for segmenting lung MRI images with fuzzy targets, weak edges, smooth boundaries, discontinuous boundaries and complex topological structures.