This book constitutes the refereed proceedings of the first MICCAI Workshop on Resource-Efficient Medical Image Analysis, REMIA 2022, held in conjunction with MICCAI 2022, in September 2022 as a hybrid event. REMIA 2022 accepted 13 papers from the 19 submissions received. The workshop aims at creating a discussion on the issues for practical applications of medical imaging systems with data, label and hardware limitations.

Magnetic resonance imaging (MRI) has emerged as a reliable tool for functional analysis of internal organs like the kidney and the heart. Due to the considerable length of time taken to acquire MR images, they are affected by patient motion. Besides, MR images are characterized by low spatial resolution, noise and rapidly changing intensity. Rapid intensity change is the primary challenge that MR image registration methods need to address. This book details some approaches to overcome this challenge. We make use of saliency information that aims to imitate the working of the human visual system for registration of medical images.The second part of our work deals with elastic registration of cardiac perfusion images. The saliency model is modified to reflect the local similarity property at every pixel. Markov random fields (MRFs) are used to integrate saliency and gradient information for elastic registration. Finally we describe a joint registration and segmentation (JRS) method for the perfusion images which exploits the mutual dependency of registration and segmentation.