Intratympanic steroid injections are commonly used for the treatment of ear diseases. During this treatment, an expert Ear, Nose & Throat (ENT) clinician delivers the drug by viewing through a large microscope that provides a close-up view of the anatomical landmarks on the middle ear. A steady hand and swift response to any patient movement are required to avoid improper placement of the needle. To assist the clinician during this treatment, a fluidic soft robot is proposed in \cite{lindenroth2021fluidic} that can steer inside a lumen for providing steady guidance for drug delivery. For robust visual guidance, stable anatomical landmarks (tympanic membrane, malleus, umbo) segmentation is required. In this work, we perform intra-domain adaptation to learn a generalized model that provides stable and consistent segmentation on unseen patients and phantom ear data
