摘要Automatic identification and segmentation of lesions in medical images has become a focus area for researchers.Segmenta-tion for medical image provides professionals with a clearer and more detailed view by accurately identifying and isolating specific tissues,organs,or lesions from complex medical images,which is crucial for early diagnosis of diseases,treatment planning,and efficacy tracking.This paper introduces a deep network based on dendritic learning and missing region detec-tion(DMNet),a new approach to medical image segmentation.DMNet combines a dendritic neuron model(DNM)with an improved SegNet framework to improve segmentation accuracy,especially in challenging tasks such as breast lesion and COVID-19 CT scan analysis.This work provides a new approach to medical image segmentation and confirms its effective-ness.Experiments have demonstrated that DMNet outperforms classic and latest methods in various performance metrics,proving its effectiveness and stability in medical image segmentation tasks.