Prediction of micro-scale bone adaptation of human trabecular bone under different implanted conditions.

Background And Objective: Different bone remodeling algorithms are used to predict bone adaptation and to understand how bones respond to the mechanical stimuli altered by implants. This paper introduces a novel micro-scale bone remodeling algorithm, which deviates from conventional methods by focusing on structure-based bone adaptation instead of density-based approaches.

Methods: The proposed model simulated cellular activities such as bone resorption, new bone formation, and maturation of newly formed bone.

A Two-Stage Noise-Tolerant Paradigm for Label Corrupted Person Re-Identification.

Supervised person re-identification (Re-ID) approaches are sensitive to label corrupted data, which is inevitable and generally ignored in the field of person Re-ID. In this paper, we propose a two-stage noise-tolerant paradigm (TSNT) for labeling corrupted person Re-ID. Specifically, at stage one, we present a self-refining strategy to separately train each network in TSNT by concentrating more on pure samples.

Reconstruction Guided Meta-Learning for Few Shot Open Set Recognition.

In many applications, we are constrained to learn classifiers from very limited data (few-shot classification). The task becomes even more challenging if it is also required to identify samples from unknown categories (open-set classification). Learning a good abstraction for a class with very few samples is extremely difficult, especially under open-set settings.

3D Printing of Ti-6Al-4V-Based Porous-Channel Dental Implants: Computational, Biomechanical, and Cytocompatibility Analyses.

Loosening of dental implants due to resorption of the surrounding bone is one of the challenging clinical complications in prosthetic dentistry. Generally, stiffness mismatch between an implant and its surrounding bone is one of the major factors. In order to prevent such clinical consequences, it is essential to develop implants with customized stiffness.

Design and manufacturing of patient-specific Ti6Al4V implants with inhomogeneous porosity.

Stress shielding remains a challenge in orthopaedic implants, including total hip arthroplasty. Recent development in printable porous implants offers improved patient-specific solutions by providing adequate stability and reducing stress shielding possibilities. This work presents an approach for designing patient-specific implants with inhomogeneous porosity.

Patient-specific femoral implant design using metamaterials for improving load transfer at proximal-lateral region of the femur.

Loading configuration of hip joint creates resultant bending effect on femoral implants. So, the lateral side of femoral implant which is under tension retracts from peri‑implant bone due to positive Poisson's ratio. This retraction of implant leads to load shielding and gap opening in proximal-lateral region, thereby allowing entry of wear particle to implant-bone interface.

Simulation and experimental investigation of the surgical needle deflection model during the rotational and steady insertion process.

Needle insertion is executed in numerous medical and brachytherapy events. Exact needle insertion into inhomogeneous soft biological tissue is of useful importance due to its significance in clinical diagnosis (especially percutaneous) and treatments. The surgical needles used in such processes can deflect during the percutaneous process.

Study of the surgical needle and biological soft tissue interaction phenomenon during insertion process for medical application: A Survey.

The insertion of the surgical needle in soft tissue has involved significant interest in the current time because of its purpose in minimally invasive surgery (MIS) and percutaneous events like biopsies, PCNL, and brachytherapy. This study represents a review of the existing condition of investigation on insertion of a surgical needle in biological living soft tissue material. As observes the issue from numerous phases, like, analysis of the cutting forces modeling (insertion), tissue material deformation, analysis of the needle deflection for the period of the needle insertion, and the robot-controlled insertion procedures.

Design of patient specific basal dental implant using Finite Element method and Artificial Neural Network technique.

The bone conditions of mandibular bone vary from patient to patient, and as a result, a patient-specific dental implant needs to be designed. The basal dental implant is implanted in the cortical region of the bone since the top surface of the bone narrows down because of aging. Taguchi designs of experiments technique are used in which 25 optimum solid models of basal dental implants are modeled with variable geometrical parameters, viz.

Probing the Influence of Hybrid Thread Design on Biomechanical Response of Dental Implants: Finite Element Study and Experimental Validation.

This study aimed to perform quantitative biomechanical analysis for probing the effect of varying thread shapes in an implant for improved primary stability in prosthodontics surgery. Dental implants were designed with square (SQR), buttress (BUT), and triangular (TRI) thread shapes or their combinations. Cone-beam computed tomography images of mandible molar zones in human subjects belonging to three age groups were used for virtual implantation of the designed implants, to quantify patient-specific peri-implant bone microstrain, using finite element analyses.

Combined computational modeling and experimental analysis integrating chemical and mechanical signals suggests possible mechanism of shoot meristem maintenance.

Stem cell maintenance in multilayered shoot apical meristems (SAMs) of plants requires strict regulation of cell growth and division. Exactly how the complex milieu of chemical and mechanical signals interact in the central region of the SAM to regulate cell division plane orientation is not well understood. In this paper, simulations using a newly developed multiscale computational model are combined with experimental studies to suggest and test three hypothesized mechanisms for the regulation of cell division plane orientation and the direction of anisotropic cell expansion in the corpus.

Probing combinational influence of design variables on bone biomechanical response around dental implant-supported fixed prosthesis.

This study aimed to understand the effect of physiological and dental implant-related parameter variations on the osseointegration for an implant-supported fixed prosthesis. Eight design factors were considered (implant shape, diameter, and length; thread pitch, depth, and profile; cantilever [CL] length and implant-loading protocol). Total 36 implantation scenarios were simulated using finite element method based on Taguchi L orthogonal array.

Text-Based Localization of Moments in a Video Corpus.

Prior works on text-based video moment localization focus on temporally grounding the textual query in an untrimmed video. These works assume that the relevant video is already known and attempt to localize the moment on that relevant video only. Different from such works, we relax this assumption and address the task of localizing moments in a corpus of videos for a given sentence query.

Design of patient specific bone stiffness mimicking scaffold.

The difference in stiffness of a patient's bone and bone implant causes stress shielding. Thus, implants which match the stiffness of bone of the patient result in better bone growth and osseointegration. Variation in porosity is one of the methods to obtain implants with different stiffness values.

Learning Person Re-Identification Models From Videos With Weak Supervision.

Most person re-identification methods, being supervised techniques, suffer from the burden of massive annotation requirement. Unsupervised methods overcome this need for labeled data, but perform poorly compared to the supervised alternatives. In order to cope with this issue, we introduce the problem of learning person re-identification models from videos with weak supervision.

Measurement of strain in the rod for lumbar pedicle screw fixation: An experimental and finite element study.

Spinal fusion with pedicle-screw-rod is being used widely for treating spinal deformities diseases. Several biomechanical studies on screw rod based implant failure through screw pullout, bending, screw breakage have been performed. But few studies are available regarding the effect of strain for breakage of rod.

Finite element and experimental analysis to select patient's bone condition specific porous dental implant, fabricated using additive manufacturing.

Background: Differences in patients' bone conditions lead to variations in the bio-mechanical environment at the peri-implant bone after implantation. It is therefore imperative to design patient-specific dental implants with customized stiffness to minimize stress shielding and better osseointegration.

Method: Nine Ti-6Al-4V implants with pore sizes of 500, 700, 900 μm and 10, 20, 30% porosity each and one non-porous (solid) implant were modelled for experimental and finite element (FE) analysis.

Design of Patient Specific Spinal Implant (Pedicle Screw Fixation) using FE Analysis and Soft Computing Techniques.

Background: This work uses genetic algorithm (GA) for optimum design of patient specific spinal implants (pedicle screw) with varying implant diameter and bone condition. The optimum pedicle screw fixation in terms of implant diameter is on the basis of minimum strain difference from intact (natural) to implantation at peri-prosthetic bone for the considered six different peri-implant positions.

Methods: This design problem is expressed as an optimization problem using the desirability function, where the data generated by finite element analysis is converted into an artificial neural network (ANN) model.

Biomechanical Analysis to Probe Role of Bone Condition and Subject Weight in Stiffness Customization of Femoral Stem for Improved Periprosthetic Biomechanical Response.

Stress shielding due to difference in stiffness of bone and implant material is one among the foremost causes of loosening and failure of load-bearing implants. Thus far, femoral geometry has been given priority for the customization of total hip joint replacement (THR) implant design. This study, for the first time, demonstrates the key role of bone condition and subject-weight on the customization of stiffness and design of the femoral stem.

Exploiting Typicality for Selecting Informative and Anomalous Samples in Videos.

In this paper, we present a novel approach to find informative and anomalous samples in videos exploiting the concept of typicality from information theory. In most video analysis tasks, selection of the most informative samples from a huge pool of training data in order to learn a good recognition model is an important problem. Furthermore, it is also useful to reduce the annotation cost as it is time-consuming to annotate unlabeled samples.

Factors Affecting Diffuse Axonal Injury under Blunt Impact and Proposal for a Head Injury Criteria: A Finite Element Analysis.

Diffuse axonal injury (DAI) is the most common pathological feature of brain injury which accounts for half of the traumatic lesions in the United States. Although direct shear strain measures indicate DAI, it is localized and varies greatly in the brain. It has limitations when correlated with the possibility and severity of DAI in different brain regions along different planes for variable factors.

Computational intelligence based design of implant for varying bone conditions.

The objective is to make the strain deviation before and after implantation adjacent to the femoral implant as close as possible to zero. Genetic algorithm is applied for this optimization of strain deviation, measured in eight separate positions. The concept of composite desirability is introduced in such a way that if the microstrain deviation values for all eight cases are 0, then the composite desirability is 1.

Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeries.

With advanced image journaling tools, one can easily alter the semantic meaning of an image by exploiting certain manipulation techniques such as copy clone, object splicing, and removal, which mislead the viewers. In contrast, the identification of these manipulations becomes a very challenging task as manipulated regions are not visually apparent. This paper proposes a high-confidence manipulation localization architecture that utilizes resampling features, long short-term memory (LSTM) cells, and an encoder-decoder network to segment out manipulated regions from non-manipulated ones.

Context-Aware Query Selection for Active Learning in Event Recognition.

Activity recognition is a challenging problem with many practical applications. In addition to the visual features, recent approaches have benefited from the use of context, e.g.