Lip Segmentation Research Articles

Retraction Note: Lip segmentation using localized active contour model with automatic initial contour

Retraction Note: Lip segmentation using localized active contour model with automatic initial contour

Description of Panagrolaimus namibiensis n. sp. (Rhabditida: Panagrolaimidae), an Anhydrobiotic Nematode from the Namib Desert of Namibia.

Panagrolaimus namibiensis n. sp. was recovered and cultured from soils collected under Arthraerua leubnitziae (pencil-bush) in the Namib Desert of Namibia, one of the driest terrestrial habitats on Earth. It is described here based on morphometrics, scanning electron micrographs, light images, line drawings, and molecular data. The new species is distinguished by having a conspicuous posterior deirid, a hook-shaped stegostomal dorsal tooth, and anterior deirids and excretory pore aligned at mid-bulb. It was morphologically compared to eleven well-described species in the genus with which it shared similar labial structure (six distinct rounded lips, and low lip segments separated in pairs), conoid tail, and/or a lateral field with three incisures, including P. labiatus, P. kolymaensis, P. davidi, P. rigidus, and P. superbus. Bayesian phylogenetic analyses using SSU and LSU rDNA each placed P. namibiensis n. sp. within clades of Panagrolaimus species, although the two trees resolved its relationship to previously described species differently. Furthermore, our analyses showed the genus is not monophyletic. In a laboratory experiment, P. namibiensis n. sp. survived exposure to 0% relative humidity for 24 h, demonstrating the anhydrobiotic ability of this species that contributes to its survival in the Namib Desert.

Effective Correction of Columellar Base Deviation in Primary Unilateral Cleft Lip Repair: A Muscle-Driven Method.

Columellar base deviation is a common and challenging deformity in patients with unilateral cleft lip. Debate continues on its surgical correction without sufficient studies to establish effective management. This article presents the authors' experience in correcting the columellar base deviation with the muscle-driven method in primary lip repair. The key is to perform extensive muscle dissection and reconstruction. In the medial lip segment, muscle dissection is performed subcutaneously up to the contralateral nostril floor for effective lengthening and rotation. In the lateral lip segment, muscle dissection is executed in both submucosal and subcutaneous planes, and muscle component is extensively separated from the lip skin and buccal mucosa. The lateral muscle flap is advanced and reattached to the contralateral nostril floor and columellar base using a subcutaneous sustaining suture. Cinching suture between columellar base and alar base is performed. These 2 sutures help centralize and overcorrect the columellar base. Bilateral muscle components are reoriented and approximated in a Z-plasty format for lengthening of the lip. The patients were followed up for at least 3 years. Quantitative measurements of deviation in columellar base angulation were taken and revealed 55.8 ± 2.6 degrees (before nasoalveolar molding), 29.6 ± 1.7 degrees (after nasoalveolar molding), and 2.8 ± 0.4 degrees (postoperative follow-up), respectively. The muscle-driven method represents a safe and effective technique to correct columellar base deviation in patients with unilateral cleft lip.

Developing a core outcome set for anthropometric evaluation for presurgical infant orthopaedics for unilateral cleft lip and palate: e-Delphi consensus

Presurgical infant orthopaedics (PSIO) in infants with cleft lip and palate focuses on improving the anatomical conditions of the lip, palate and nose before the first lip surgery; however, its effectiveness has not been proven. To develop a core outcome set for reporting anthropometry-based outcomes in studies appraising the PSIO before primary cleft lip repair in unilateral cleft lip palate (UCLP). Literature search to identify anthropometric measures. The operational definition and schematic representation of each were elaborated, grouping those apparently the same. By using Delphi methodology with a consensus of 10 subject-matter experts, three rounds were conducted to select a core outcome set of anthropometric measures with a validity V coefficient ≥80% among considered necessary to evaluate the PSIO in UCLP. A total of 101 anthropometric measures were identified in the literature to evaluate PSIO in UCLP. Of these, consensus validated the content of the core outcome set, which comprises 18 anthropometric measures, including columella height, nasal tip projection, projection alar length, width of nostril, nasal basal width, angle of columella, cleft lip segment, height of the non-cleft lip, height of the cleft lip, intersegment distance, arch length, greater segment length, lesser segment length, lateral deviation of the incisal point, posterior width of palatal cleft, arch width, grater segment rotation and lesser segment rotation. Standardised outcome measures are necessary to evaluate and ensure the quality of treatment in CLP. The core outcome set for anthropometric evaluation validated by consensus subject-matter experts is a clinically useful and low-cost tool for PSIO effectiveness studies.

Lip reading of words with lip segmentation and deep learning

Lip reading of words with lip segmentation and deep learning

Primary Repair of Bilateral Cleft Lip Deformity and Absent Prolabium With a Full-Thickness Skin Graft.

Bilateral cleft lip deformities makeup 10% of orofacial clefts and are uncommon when compared to unilateral cleft lip.1,2 These cleft deformities have significant physical and long-term psychosocial effects on not only the patient but their family. With bilateral cleft lip deformity, the cutaneous approximation of the lateral lip segments are dependent on a sufficient prolabium to reconstruct the philtrum.3,4 Deficient skin equates to tight midline closure and subsequent unsightly scarringIn the subclinical phenotype of bilateral cleft lip and palate, where the patient has an absent or deficient prolabium, achieving tension free closure in the primary surgical setting is a reconstructive dilemma.5 This clinical report describes the use of a full-thickness skin graft to reconstruct the philtrum in a 12-month-old boy with bilateral cleft lip deformity, absent prolabium, absent columella and absent nasal septum to provide an aesthetic subunit repair.

Lip Reading using Local-Adjacent Feature Extractor and Multi-Level Feature Fusion

Lip reading is a widely used technology, which aims to infer text content from visual information. To represent lip information more efficiently and reduce the network parameters, most networks will first extract features from lip images and then classify the features. In recent studies, most researchers adopt convolutional networks to extract information from pixels which contain a lot of useless information, limiting the improvement of model accuracy. In this paper, we designed a graph structures and a lip segmentation network to effectively represent changes in the shape of the lips in adjacent frames and the ROI in local frame and propose two feature extractors, named U-net-based local feature extractor and graph-based adjacent feature extractor. We proposed a very challenging dataset to simulate extreme environments, including highly variable face properties, light intensity and so on. Finally, we designed several different levels of feature fusion methods. The experimental results on the proposed challenging dataset show that the model can effectively extract the useful information from content irrelevant information very well. The accuracy of our proposed model is 9.1% higher than that of baseline. This result shows that our proposed model can better adapt to the application of the wild environment.

Threshold-based outer lip segmentation using support vector regression

Automated lip reading from videos requires lip segmentation. Threshold-based segmentation is straightforward, but it is rarely used. This study proposes a histogram threshold based on the feedback of shape information. Both good and bad lip segmentation examples were used to train an \(\epsilon \)-support vector regression model to infer the segmentation accuracy from the region shape. The histogram threshold was optimised to minimise the segmentation error. The proposed method was tested on 895 images from 112 subjects using the AR Face Database. The proposed method, implemented in simple segmentation algorithms, reduced segmentation errors by 23.1%.

One Shot Segmentation: Unifying Rigid Detection and Non-Rigid Segmentation Using Elastic Regularization.

This paper proposes a novel approach for the non-rigid segmentation of deformable objects in image sequences, which is based on one-shot segmentation that unifies rigid detection and non-rigid segmentation using elastic regularization. The domain of application is the segmentation of a visual object that temporally undergoes a rigid transformation (e.g., affine transformation) and a non-rigid transformation (i.e., contour deformation). The majority of segmentation approaches to solve this problem are generally based on two steps that run in sequence: a rigid detection, followed by a non-rigid segmentation. In this paper, we propose a new approach, where both the rigid and non-rigid segmentation are performed in a single shot using a sparse low-dimensional manifold that represents the visual object deformations. Given the multi-modality of these deformations, the manifold partitions the training data into several patches, where each patch provides a segmentation proposal during the inference process. These multiple segmentation proposals are merged using the classification results produced by deep belief networks (DBN) that compute the confidence on each segmentation proposal. Thus, an ensemble of DBN classifiers is used for estimating the final segmentation. Compared to current methods proposed in the field, our proposed approach is advantageous in four aspects: (i) it is a unified framework to produce rigid and non-rigid segmentations; (ii) it uses an ensemble classification process, which can help the segmentation robustness; (iii) it provides a significant reduction in terms of the number of dimensions of the rigid and non-rigid segmentations search spaces, compared to current approaches that divide these two problems; and (iv) this lower dimensionality of the search space can also reduce the need for large annotated training sets to be used for estimating the DBN models. Experiments on the problem of left ventricle endocardial segmentation from ultrasound images, and lip segmentation from frontal facial images using the extended Cohn-Kanade (CK+) database, demonstrate the potential of the methodology through qualitative and quantitative evaluations, and the ability to reduce the search and training complexities without a significant impact on the segmentation accuracy.

Design and Experimental Characterization of an Actuation System for Flow Control of an Internally Blown Coanda Flap

The focus of the work is on the evaluation, development and integration of a robust actuator system for three-dimensional flow control of a blown Coanda flap to improve the high lift system of commercial aircraft. As part of the research work presented, the system is integrated into a wind tunnel model in order to influence the flow across the entire width of the model. The system developed is based on individual bending transducers that can vary the height of the blowing slot dynamically. The system is divided into 33 segments and is therefore able to implement static and dynamic actuation along the wing-span (3D-actuation). All segments can be controlled independently and thus offer great optimization potential for an effective flow control. Different configurations were developed and evaluated against each other with respect to the demanding requirements (small installation space, frequency range from 5 Hz to 300 Hz, 1 bar pressure, 0.4 mm deflection, 1 m span). The design of the blown flap has been specified in an iterative design process. In the final configuration, all mechanical components are reduced to the bare minimum for weight reduction reasons, in order to meet the dynamic requirements of the wind tunnel model. To characterize the lip segments, a test device has been designed that can be pressurized to generate aerodynamic loads on the lip segments. Finally, 33 lip segments were integrated into a wind tunnel model and tested intensively as part of a measurement campaign. The first aerodynamic results show an increase in lift of up to ∆Ca = 0.57. These aerodynamic gains are achieved at amplitudes that do not require the lip segments to completely close or open the blowing slot, which shows the advantage of the current lip design that enables activation with independently controlled stationary and unsteady components.

A Review on Nasoalveolar Molding

ABSTRACTA common hereditary defect of the oral cavity with grave socioeconomic problem is cleft lip and palate. Although the defect varies in forms and severity, the individuals presented with glitches regarding functions and esthetics. Authors claim that nasoalveolar molding improves facial esthetics and function and has gained more attention. The objective of presurgical nasoalveolar molding comprises improving lip segment, inferior lateral alar cartilages, and alveolar cleft segments. Outcomes of presurgical nasoalveolar molding are promising and hence are encouraged immediately after birth and continued until further corrective surgery is planned. The rationale of presurgical nasoalveolar molding is approximation of the alveolar segments, wherein the surgeon has to perform gingivoperiosteoplasty followed by corrective lip surgery.How to cite this article:Manivannan P, Alexander L, Vijaykumar V. A Review on Nasoalveolar Molding. J Sci Dent 2020;10(2):49–50.

A new technique for perioral muscle reconstruction and lip lengthening in complete unilateral cleft lip

BackgroundAdequate skin lengthening and symmetry may not be consistently obtained in unilateral cleft lip repair, especially in patients with complete cleft. The purpose of this study was to present the model of muscle dissection and approximation to facilitate lip lengthening and symmetry. MethodsThe design followed the rotation-advancement (RA) method without skin measurement. A curvilinear skin incision was made from subnasale to the Cupid's bow peak (CBP). Muscle dissection was continued to the contralateral nostril floor beneath the columellar base to facilitate downward rotation in the medial lip. Wide muscle dissection was performed in the lateral lip segment from the nasal mucosa passing the alar base. The lateral lip muscle was advanced and sutured to the medial lip muscle in a Z-plasty fashion. A small skin backcut was made above the CBP. Primary nasal correction was performed. A series of 138 patients with complete unilateral cleft lip and palate were included in this study. Standard photographs were collected for measurement in the nasolabial region. ResultsAdequate lengthening and symmetry of the lip was obtained. The ratio of vertical philtral height was 0.99±0.05 between the cleft and noncleft sides. The C flap was used for supplementary skin lengthening in 58% of cases. Postoperative lip retraction requiring massage occurred in 13%. Overall nasolabial appearance was satisfactory. ConclusionThe new technique of perioral muscle reconstruction facilitated to obtain lip lengthening and symmetry in the repair of complete unilateral cleft lip.

A Spectacular New Species of Habenaria (Orchidaceae) From Southern Brazilian Amazon

Abstract—A new Habenaria species from the state of Mato Grosso is described and illustrated. Habenaria gracilisegmenta was discovered in campinarana understory, in northern Mato Grosso state, on the southern edge of the Brazilian Amazon. The species is distinguished by its slender habit, and by the few, delicate flowers, with very long, thin lateral petals and lip segments. Its morphological affinity with other Neotropical species is unclear. A molecular phylogenetic analysis revealed that the new species does not belong to any of the Neotropical subclades of the genus, constituting an additional lineage. The species is one of two of the genus endemic to the Brazilian Amazon, and considered threatened given the small number of known populations and restricted distribution.

Efficient Scale Invariant and Back Propagation Neural Network Method using LIP Region Segmentation

With the advent of technological sensor devices and human interface machine technology, there has been extensive research done in lip segmentation methods by several researchers — some linguistic features required for interaction with the machine equipment. Therefore, research work has been done in the audio speech detection scheme for recognition of lip reading. Visual lip reading technology developed based on the extraction of features of the lip. Lip segmentation is an essential approach to recognize lip reading scheme. Meanwhile, it helps to improve parameters. Several methods studied to segment the lip area based on localized active contour method using twice contour finding and combined color-space method. Apply the illumination histogram equalization to real color images to reduce the distortion of uneven illumination. The proposed method implemented can get better accuracy rate and segmentation results and compare with the existing process using area or circle as the region to segment grayscale images and combined in the color-space image. Using SIFT and BPNN, the inner region of the lip found in the result. The experiment tool is used MATLAB 2016a and designs a PROJECT APPLICATION. Improve the success rate and reduce the segmented error and compared with the current metrics. The experimental analysis determines the accuracy rate with 94%; error rate reduces with Segmented Error % and Overlap Error rate value with 79.73%.

Quantitative Effects of Cleft Lip and Nose Adhesion on Nostril and Alveolar Discrepancy

BACKGROUND: Although there are considerable data quantifying the effects of nasoalveolar molding on definitive lip repair, less is known about the effect of cleft lip and nose adhesion (CLNA) on the alveolar segments and nostril shape in patients who are unable to undergo craniofacial orthodontics. CLNA approximates the lip segments, resulting in the conversion of a complete cleft lip to an incomplete cleft lip while sparing the tissues and landmarks for eventual definitive lip repair. In resource-constrained environments or situations where patients cannot undergo craniofacial orthodontics, CLNA has been shown to qualitatively improve nostril shape before definitive reconstruction in wide cleft. However, less is known about the effects of CLNA alone on the nostril and alveolar cleft segments dimensions. MATERIALS AND METHODS: After obtaining Institutional Review Board approval, a single-center retrospective review of unilateral cleft lip patients undergoing CLNA was performed. Measurements were taken at the time of CLNA and at formal repair. The following data points were extracted for the cleft and noncleft side: nostril height (NH), nostril width (NW), alveolar height (AH), and alveolar width (AW). Dimensional changes from the time of CLNA and time of formal repair were statistically analyzed using a paired Student’s t test. RESULTS: A total of 1,053 surgical cases were reviewed. Eight patients met criteria for inclusion. Average NH before CLNA was 2.3 mm on the cleft side and 5.6 mm on the noncleft side (P = 0.020). After CLNA, the NH on the cleft versus noncleft side was 4.5 and 5.0 mm, respectively (P = 0.553). Average NW before CLNA was 14.8 mm on the cleft side, compared to 7.3 mm on the noncleft side (P = 0.003). After CLNA, the average NW on the cleft side was 11.2 mm, compared to 7.1 mm on the noncleft side (P = 0.007). CLNA resulted in a significant reduction in NW on the cleft side (P = 0.002). The average AW discrepancy, measured as the gap between alveolar segments, was 9.9 mm before CLNA and significantly decreased to 1.5 mm before definitive repair (P = 0.002). AH discrepancy decreased from 11.4 to 6.5 mm (P = 0.060). CONCLUSION: This study reports quantitative changes with CLNA, a powerful tool for reshaping the nostril and approximating the alveolar segments in cases where nasoalveolar molding is not an option. This study demonstrates that CLNA alone achieves a cleft NH which approaches the noncleft side, improved AH and width discrepancy by closure of the gap between alveolar segments, and significant reduction in NW.

Unsupervised lip segmentation based on quad-tree MRF framework in wavelet domain

In this paper, we propose a new extended method to implement lip segmentation. Based on a quad-tree structure (QTS) Markov random field (MRF) model under unsupervised situation, the proposed method achieves the lip segmentation in wavelet domain. Firstly, we set up a multi-layer hierarchical model, in which each pixel of every layer corresponds to the four nodes in quad-tree structure. Then the probability of a branch node can be calculated by using the probability of the previous branch node through the tree structure easily. Subsequently, a Markov random field derived from the model is obtained so that the segmentation problem is formulated as a labeling optimization problem in the framework of the maximum a posteriori Markov random field (MAP-MRF). Assuming that the pre-assigned cluster of data segments may overestimate the underlying fact, and leads to over-segmentation, we propose a variable-weight segmentation approach to improve the robustness of the segmentation. The experimental results show that this method has better segmentation accuracy than traditional methods.

Lip image segmentation based on a fuzzy convolutional neural network

Research has shown that the human lip and its movements are a rich source of information related to speech content and speaker's identity. Lip image segmentation, as a fundamental step in many lip-reading and visual speaker authentication systems, is of vital importance. Because of variations in lip color, lighting conditions and especially the complex appearance of an open mouth, accurate lip region segmentation is still a challenging task. To address this problem, this article proposes a new fuzzy deep neural network having an architecture that integrates fuzzy units and traditional convolutional units. The convolutional units are used to extract discriminative features at different scales to provide comprehensive information for pixel-level lip segmentation. The fuzzy logic modules are employed to handle various kinds of uncertainties and to provide a more robust segmentation result. An end-to-end training scheme is then used to learn the optimal parameters for both the fuzzy and the convolutional units. A dataset containing more than 48 000 images of various speakers, under different lighting conditions, was used to evaluate lip segmentation performance. According to the experimental results, the proposed method achieves state-of-the-art performance when compared with other algorithms.

Presurgical Nasoalveolar Molding in a 4-day-old Infant with Unilateral Cleft Lip, Alveolus, and Palate Deformity

Introduction A four day old male infant was referred to our department. Infant’s mother complained of an opening over lip and difficulty in feeding and desires to get it corrected. On clinical examination patient showed complete unilateral cleft lip, alveolus and palate deformity towards the left side. Methods On the initial visit, lip taping using 1/4inch 3M Steri-strip was applied and instructions were given to parents about lip taping, and advised to continue lip taping for 2 weeks. Initial impressions were taken to fabricate the Presurgical nasoalveolar molding appliance. Intraoral molding plate was made to approximate the maxillary segments. Nasal stent was added to correct the nose deformity. Presurgical impressions were made. Results Under this pre surgical treatment, the cleft alveolus reduced in size from 13mm to 3mm at the alveolar ridge and palate, respectively. The nasal wing was lifted considerably. Conclusion Pre-surgical nasoalveolar moulding helped to reduce the cleft gap, improve the arch form, approximate lip segments and distinctly improve the morphology of the nose by correcting flattened nasal wings. This aforementioned correction not only enabled better aesthetic results after surgery but also reduced tissues tension and scar formation post-surgery.

Lip Segmentation Based on Combined Color Space and ACM with Rhombic Initial Contour

Lip segmentation is one of critical steps in a lip-reading system, because it closely relates to the accuracy of system recognition. In this paper, we aim to improve the accuracy of lip segmentation. A novel color space is proposed which consists of the [Formula: see text] component in the CIE-LUV space and the sum of [Formula: see text]2 and [Formula: see text]3 components of the image after discrete Hartley transform (DHT). We select a rhombus as the initial contour as its shape is approximate to a closed lip shape relatively. These notions are achieved based on the method of the Active contour model. The active contour model (ACM) is performed by the Chan–Vese model, and the result of each component is gained separately. Finally, the ultimate results are obtained by merging the result of each component together. Through experiments we can get a conclusion that this method can get more accurate and smoother lip contour. Meanwhile, the proposed method is more efficient compared with the classic ACM because it avoids some problems in the classic active contour model, like the radius of the initial contour needs to be set manually according to the size of images.

Eye and mouth state detection algorithm based on contour feature extraction

Eye and mouth state analysis is an important step in fatigue detection. An algorithm that analyzes the state of the eye and mouth by extracting contour features is proposed. First, the face area is detected in the acquired image database. Then, the eyes are located by an EyeMap algorithm through a clustering method to extract the sclera-fitting eye contour and calculate the contour aspect ratio. In addition, an effective algorithm is proposed to solve the problem of contour fitting when the human eye is affected by strabismus. Meanwhile, the value of chromatism s is defined in the RGB space, and the mouth is accurately located through lip segmentation. Based on the color difference of the lip, skin, and internal mouth, the internal mouth contour can be fitted to analyze the opening state of mouth; at the same time, another unique and effective yawning judgment mechanism is considered to determine whether the driver is tired. This paper is based on the three different databases to evaluate the performance of the proposed algorithm, and it does not need training with high calculation efficiency.