A method is investigated for high-sensitivity detection of slight deformations, such as defects on semiconductor wafers, using multiple scanning electron microscope (SEM) images. The relationship between the signal-to-noise ratio (S/N) for shape deformation and the solid angle of electron detection is investigated using an SEM simulator to overcome the problem of low S/N in SEM images of slight shape deformations obtained using conventional SEMs. Based on the investigation, we proposed a new defect detection algorithm. Three SEM images are simultaneously acquired from a die; from these, two images are synthesized—one for enhancing deformation and one for enhancing material contrast—by a linear combination. Three more images are then acquired from the neighboring die and two images are synthesized in the same way. The images from the two dies are compared in a two-dimensional vector space spanned by the intensities of the two synthesized images to discriminate defects. Experimental results obtained using an actual SEM demonstrate that the proposed method is effective in detecting slight deformations.