The field of medical image analysis and registration is moving towards more accurate and robust methods for estimating patient pose and shape, registering images, and analyzing breast deformations during radiotherapy. Innovative approaches, such as multi-modal networks and spatial-awareness convolutions, are being developed to address challenges like occlusions and partial volume effects. These advances have the potential to improve clinical outcomes in perioperative care, breast cancer treatment, and total hip arthroplasty. Notable papers include: SACB-Net, which introduces a spatial-awareness convolution block for medical image registration, and the surface guided analysis of breast changes during post-operative radiotherapy, which proposes a geometric approach to analyze inter-fractional breast deformation. The divide to conquer approach for multi-organ whole-body CT image registration also shows promise in handling complex deformations.