Research on bone reconstruction is generally limited to simple fractures from a small number of fragments. Recent advances in augmented reality real-time solutions for robotic surgery navigation with modular approach during invivo robotic surgery and segmentation of the whole procedure in a set of stages allow for a very good tracking strategy for fracture reconstruction. The scientific literature on semi-automatic or fully automatic reconstruction of bone fragments is quite scarce, with research mainly on medical imaging, bone segmentation and surface recording. Patients may require reconstructive surgery, with multiple interventions over a longer period of time, to maintain the joint function or even the joint replacement. Its effect is a decrease in general health, loss of work capacity, or even disability. This is a serious health condition comparable to other major disorders, such as stroke, heart disease or diabetes. Severe joint fractures occur most frequently in young adult patients, and the objectives of treatment are to stabilize the patient and achieve a bone union as quickly as possible, in a position of alignment of the limbs, and avoid posttraumatic osteoarthritis. Exact bone restoration allows the reconstruction of the axes, being a critical factor in determining the favorable clinical prognosis. Injuries resulting in fractures of the joints, such as the knee, can lead to fragmented bones, which require precise surgical reconstruction.

Computer Assisted Diagnosis systems based on convolutional neural network are limiting the number of wrong diagnoses and can be used for improving diagnosis accuracy, as demonstrated for proximal femur fractures that is aimed to be extended to all bone segments, and to become a tool commonly used in hospital practice.

Even if personalized web-based predictive tools in orthopedic surgery are becoming increasingly available, fractures are often difficult to detect and analyze on film scans. Also, bone density disorders may lead to an increase in the probability of unexpected fractures, or the association between bone and muscle tissue reduction with risk factors for some chronic diseases. Serious trauma suffered as a result of vehicle accidents or falls from heights in which a large amount of energy is involved often results in fractures in which bones are multifragmentary. The method is validated in practice for preoperative planning of a 49-year-old male patient who had a tibial plateau fracture of Schatzker type VI. The paper solves a challenging problem for the reconstruction of fractured bones, namely the choice of the optimal matching option from the situation in which surface portions of a fracture fragment correspond to multiple high fragments. The final matching and the right alignment are performed automatically by the innovative alignment algorithm. Positional uncertainties are eliminated interactively by the user, who selects the corresponding pairs of fracture surfaces. The provided solution is able to align the surfaces of bone fragments derived from the segmentation process of volumetric tomographic data. We have created a structured integration process and an alignment algorithm integrated in a clinical workflow for personalized surgical treatment of fractures. The aim of this paper is to develop a new method of aligning fragments of comminutive fractures. Scientific literature describes some semi-automatic reconstructive attempts at fragmented bone fractures, but the matching algorithms presented are likely to improve. The planning of the surgical treatment in orthopedics, with the help of three-dimensional (3D) technologies, arouses an increasing scientific interest.

Allignment function meshlab