Facial Paralysis Grading Based on Dynamic and Static Features

Peripheral facial nerve palsy, also known as facial paralysis (FP), is a common clinical disease, which requires subjective judgment and scoring based on the FP scale. There exists some automatic facial paralysis grading methods, but the current methods mostly only consider either static or dynamic features, resulting in a low accuracy rate of FP grading. This thesis proposes an automatic facial paralysis assessment method including both static and dynamic characteristics. The first step of the method performs preprocessing on the collected facial expression videos of the subjects, including rough video interception, video stabilization, keyframe extraction, image geometric normalization and gray-scale normalization. Next, the method selects as keyframes no facial expression state and maximum facial expression state in the image data to build the the research data set. Data preprocessing reduces errors, noise, redundancy and even errors in the original data. The basis for extracting static and dynamic features of an image is to use Ensemble of Regression Trees algorithm to determine 68 facial landmarks. Based on landmark points, image regions of image are formed. According to the Horn-Schunck optical flow method, the optical flow information of parts of the face are extracted, and the dynamic characteristics of the optical flow difference between the left and right parts are calculated. Finally, the results of dynamic and static feature classification are weighted and analyzed to obtain FP ratings of subjects. A 32-dimensional static feature is fed into the support vector machine for classification. A 60-dimensional feature vector of dynamical aspects is fed into a long and short-term memory network for classification. Videos of 30 subjects are used to extract 1419 keyframes to test the algorithm. The accuracy, precision, recall and f1 of the best classifier reach 93.33%, 94.29%, 91.33% and 91.87%, respectively.Perifeerinen kasvojen hermohalvaus, joka tunnetaan myös nimellä kasvojen halvaus (FP), on yleinen kliininen sairaus, joka vaatii subjektiivista arviointia ja FP -asteikon pisteytystä. Joitakin automaattisia kasvohalvauksen luokittelumenetelmiä on olemassa, mutta yleensä ottaen ne punnitsevat vain joko staattisia tai dynaamisia piirteitä. Tässä tutkielmassa ehdotetaan automaattista kasvojen halvaantumisen arviointimenetelmää, joka kattaa sekä staattiset että dynaamiset ominaisuudet. Menetelmän ensimmäinen vaihe suorittaa ensin esikäsittelyn kohteiden kerätyille kasvojen ilmevideoille, mukaan lukien karkea videon sieppaus, videon vakautus, avainruudun poiminta, kuvan geometrinen normalisointi ja harmaasävyjen normalisointi. Seuraavaksi menetelmä valitsee avainruuduiksi ilmeettömän tilan ja kasvojen ilmeiden maksimitilan kuvadatasta kerryttäen tutkimuksen data-aineiston. Tietojen esikäsittely vähentää virheitä, kohinaa, redundanssia ja jopa virheitä alkuperäisestä datasta. Kuvan staattisten ja dynaamisten piirteiden poimimisen perusta on käyttää Ensemble of Regression Trees -algoritmia 68 kasvojen merkkipisteiden määrittämiseen. Merkkipisteiden perusteella määritellään kuvan kiinnostavat alueet. Horn-Schunckin optisen virtausmenetelmän mukaisesti poimitaan optisen virtauksen tiedot joistakin kasvojen osista, ja dynaaminen luonnehdinta lasketaan vasempien ja oikeiden osien välille. Lopuksi dynaamisen ja staattisen piirteiden luokittelun tulokset painotetaan ja analysoidaan kattavasti koehenkilöiden FP-luokitusten saamiseksi. 32- ulotteinen staattisten piirteiden vektori syötetään tukivektorikoneeseen luokittelua varten. 60-ulotteinen dynaamisten piirteiden ominaisuusvektori syötetään pitkän ja lyhyen aikavälin muistiverkkoon luokittelua varten. Parhaan luokittelijan tarkkuus, täsmällisyys, palautustaso ja f1 saavuttavat arvot 93,33%, 94,29%, 91,33% ja 91,87%

A pilot study on automated quantitative grading of facial functions

Quantitative grading of facial paralysis (FP) and the associated loss of facial function are essential to evaluate the severity and to track deterioration or improvement of the condition following treatment. To date, several computer-assisted grading systems have been proposed but none have gained widespread clinical acceptance. There is still a need for an accurate quantitative assessment tool that is automatic, inexpensive, easy to use, and has low inter-observer variability. The aim of the authors is to develop such a comprehensive Automated Facial Grading (AFG) system. One of this system’s modules: the resting symmetry module has already been presented. The present study describes the implementation of the second module for grading voluntary movements. The system utilizes the Kinect v2 sensor to detect and capture facial landmarks in real time. The functions of three regions, the eyebrows, eyes and mouth, are evaluated by quantitatively grading four voluntary movements. Preliminary results on normal subjects and patients are promising. The AFG system is a novel system that is suitable for clinical use because it is fast, objective, easy to use, and inexpensive. With further enhancement, it can be extended to become a virtual facial rehabilitation tool

MANDIBULAR SHAPE IN MYOSTATIN-DEFICIENT MICE: A GEOMETRIC MORPHOMETRIC ANALYSIS

The relationship between muscle function and mandibular morphology is unclear. Manipulating the size or function of muscle and then observing the effect on adjacent bone is one way to explore this relationship. The premise is that muscles under function create stress and strain on bone, thereby altering bone morphology. Myostatin knockout (MKO) mice are hypermuscular and may be used as an animal model to study this muscle-bone association. Previous studies comparing MKO mice have used conventional cephalometric analyses to compare their skeletal morphology to wild-type controls. The objective of our study is to provide a phenotypic description of the mandible in MKO mice compared to wild-type CD-1 control mice by quantifying their shape variation at 28 days of age utilizing a geometric morphometric approach. The hypothesis proposes that epigenetic muscle-bone interactions during development cause mandibular shape changes in MKO mice compared to the wild-type controls by 28 days of age. The present sample included nine wild-type and eight MKO mice 28 days old. Eleven mandibular landmarks were recorded on each cephalogram. The landmarks were aligned using Procrustes superimposition method and new coordinates were created to perform a canonical variates analysis (CVA). Results found a significant difference in the mean mandibular shape between the MKO and wild-type groups (Procrustes statistic: 0.047; p = 0.014). The inferior border of the mandible of the myostatin-deficient mice showed increased curvature and decreased ramal height when compared to the wild-type mice. The curved mandible phenotype here may be analogous to the ‘rocker’ mandible reported to be prominent in the Polynesian population. These findings suggest that changing muscular forces altered mandibular morphology most dramatically in regions associated with masticatory muscle attachments

Variations in the morphology of stylomastoid foramen: a possible solution to the conundrum of unexplained cases of Bell’s palsy

Background: Stylomastoid foramen is the terminal part of facial canal and is the exit gateway for facial nerve from skull base. We hypothesized that anatomical variations of this foramen could be a risk factor for the injury of facial nerve resulting in unilateral facial nerve paralysis or Bell’s palsy. Hence the present study was conducted to study the variations in size and shape of stylomastoid foramen in dry adult human skulls. Materials and methods: The study was conducted on 37 dry adult human skulls of unknown age and sex. High resolution images of the skulls under study were processed by ImageJ software and observations were undertaken. Results: Total eight variations of stylomastoid foramen were observed in terms of shape. The common variants were round, oval and square (present in 83.79% skulls on right side and 81.07% skulls on left side), whereas the rare variants were triangular, rectangular, serrated, bean-shaped and irregular. It was noted that stylomastoid foramen were associated with extensions (45.95% skulls) and also adjacent foramen (18.92% skulls). Exclusively unilateral observations included bifurcation of foramen (16.22% skulls), foramen situated deep inside skull groove (5.41% skulls) and foramen interrupted by bony spur (2.7% skulls). No significant differences were observed between the mean diameters (antero-posterior and transverse) of the stylomastoid foramen. Conclusions: The unilateral variations along with rare variations in terms of shape such as serrated, bean-shaped and irregular foramen (which were also unilateral findings) could be potential risk factors towards injury of facial nerve at the point of exit from skull base leading to Bell’s palsy