# 3D Ultrasound Mosaic of the Whole Shoulder: A Feasibility Study
The shoulder US protocols that sonographers use focus on the biceps tendon, subscapularis tendon, supraspinatus tendon, infraspinatus tendon, glenoid labrum, suprascapular notch, acromio clavicular joint and subacomial-subbelttoid bursa [8; 9; 10]. For each of these landmarks, multiple scan angles are typically employed to minimise the issues reported in the previous paragraphs and ensure that artefacts are properly identified and distinguished from pathology [8; 9; 10]. Moreover, when assessing the subacomial impingement, dynamic US examination becomes necessary [8; 9; 10]. This is achieved by having the sonographer monitor the subacomial-subbelttoid bursa while the patient is performing a sequence of shoulder movements [8; 9; 10]. There are literature reports on the US mosaic reconstruction of the liver and kidneys by using an optically tracked 3D US probe and experimenting with various registration techniques [16]. Ref. [17] registered multiple 3D cardiac US volumes using US probe tracking in order to compare various US volume compounding techniques (volume merging techniques) and assessed the resultant combined volumes with the help of 3D US experienced clinicians. Another example is the use of high-refresh-rate 3D US and its registration to MRI data in specific applications, such as the reconstruction of the intra-articular anatomy of the knee for arthroscopy [18]. Similarly, [19; 20; 21; 22] registered intraoperative 3D US data to preoperative MRI and CT data for assisting and automating surgeries. But the literature on the registration of 3D US images of the shoulder or volumetric reconstruction of the rotator cuff is very limited. US volume registration can be automated [23]. However, registrations typically rely on segmented US images, other imaging modalities and tracking systems which impose limitations on the US image acquisition and add labour to the post-process operations. The amount of work required to segment the external modalities and US images as well as perform the registrations is typically significant [17; 19; 20; 22; 24; 25; 26; 27]. This work investigates the feasibility of employing manual 3D US-US registration to reconstruct a single clinically viable US volume (a mosaic) of the entire rotator cuff region, which could be used to reduce the clinical competency needed to acquire and interpret shoulder US data and offer a CT/MRI-like view of the anatomical region. This study utilises expert sonographers and clinicians and corresponding participant shoulder MRI data to validate the clinical usefulness and reconstruction accuracy of the mosaic. This way, US can be more viable for pre-operative and intraoperative surgical planning and becomes more display-friendly for patients being examined and novice US learners. This work is preparatory for the ultimate goal of training a deep learning algorithm to automatically register US shoulder mosaics in real-time. The main significance of this study lies in the newfound understanding that by combining information from multiple 3D US volumes, all the necessary structures in the shoulder can be effectively visualised. This insight suggests that with improvements implemented to the hardware and algorithms utilising the newly discovered challenges, once sufficient US mosaic data have been collected for multiple participants, a deep learning-based 3D US registration algorithm may be trained to reconstruct 3D US shoulder mosaics in real-time, addressing all the previously discussed gaps.