Crowdsourced human-based computational approach for tagging peripheral blood smear sample images from Sickle Cell Disease patients using non-expert users.

In this paper, we present a human-based computation approach for the analysis of peripheral blood smear (PBS) images images in patients with Sickle Cell Disease (SCD). We used the Mechanical Turk microtask market to crowdsource the labeling of PBS images. We then use the expert-tagged erythrocytesIDB dataset to assess the accuracy and reliability of our proposal. Our results showed that when a robust consensus is achieved among the Mechanical Turk workers, probability of error is very low, based on comparison with expert analysis. This suggests that our proposed approach can be used to annotate datasets of PBS images, which can then be used to train automated methods for the diagnosis of SCD. In future work, we plan to explore the potential integration of our findings with outcomes obtained through automated methodologies. This could lead to the development of more accurate and reliable methods for the diagnosis of SCD.

Sickle-cell disease diagnosis support selecting the most appropriate machine learning method: Towards a general and interpretable approach for cell morphology analysis from microscopy images.

In this work we propose an approach to select the classification method and features, based on the state-of-the-art, with best performance for diagnostic support through peripheral blood smear images of red blood cells. In our case we used samples of patients with sickle-cell disease which can be generalized for other study cases. To trust the behavior of the proposed system, we also analyzed the interpretability. We pre-processed and segmented microscopic images, to ensure high feature quality. We applied the methods used in the literature to extract the features from blood cells and the machine learning methods to classify their morphology. Next, we searched for their best parameters from the resulting data in the feature extraction phase. Then, we found the best parameters for every classifier using Randomized and Grid search. For the sake of scientific progress, we published parameters for each classifier, the implemented code library, the confusion matrices with the raw data, and we used the public erythrocytesIDB dataset for validation. We also defined how to select the most important features for classification to decrease the complexity and the training time, and for interpretability purpose in opaque models. Finally, comparing the best performing classification methods with the state-of-the-art, we obtained better results even with interpretable model classifiers.

Crowdsourcing human-based computation for medical image analysis: A systematic literature review.

Computer-assisted algorithms for the analysis of medical images require human interactions to achieve satisfying results. Human-based computation and crowdsourcing offer a solution to this problem. We performed a systematic literature review of studies on crowdsourcing human-based computation for medical image analysis based on the guidelines proposed by Kitchenham and Charters. We identified 43 studies relevant to the objective of this research. We determined three primary purposes and problems that crowdsourcing human-based computation systems can solve. We found that the users provided five information types. We compared systems that use pre-, post-evaluation and quality control methods to select and filter the user inputs. We analyzed the metrics used for the evaluation of the crowdsourcing human-based computation system performance. Finally, we identified the most popular crowdsourcing human-based computation platforms with their advantages and disadvantages.Crowdsourcing human-based computation systems can successfully solve medical image analysis problems. However, the application of crowdsourcing human-based computation systems in this research area is still limited and more studies should be conducted to obtain generalizable results. We provided guidelines to practitioners and researchers based on the results obtained in this research.

Diagnosis support of sickle cell anemia by classifying red blood cell shape in peripheral blood images.

Red blood cell (RBC) deformation is the consequence of several diseases, including sickle cell anemia, which causes recurring episodes of pain and severe pronounced anemia. Monitoring patients with these diseases involves the observation of peripheral blood samples under a microscope, a time-consuming procedure. Moreover, a specialist is required to perform this technique, and owing to the subjective nature of the observation of isolated RBCs, the error rate is high. In this paper, we propose an automated method for differentially enumerating RBCs that uses peripheral blood smear image analysis. In this method, the objects of interest in the image are segmented using a Chan-Vese active contour model. An analysis is then performed to classify the RBCs, also called erythrocytes, as normal or elongated or having other deformations, using the basic shape analysis descriptors: circular shape factor (CSF) and elliptical shape factor (ESF). To analyze cells that become partially occluded in a cluster during sample preparation, an elliptical adjustment is performed to allow the analysis of erythrocytes with discoidal and elongated shapes. The images of patient blood samples used in the study were acquired by a clinical laboratory specialist in the Special Hematology Department of the "Dr. Juan Bruno Zayas" General Hospital in Santiago de Cuba. A comparison of the results obtained by the proposed method in our experiments with those obtained by some state-of-the-art methods showed that the proposed method is superior for the diagnosis of sickle cell anemia. This superiority is achieved for evidenced by the obtained F-measure value (0.97 for normal cells and 0.95 for elongated ones) and several overall multiclass performance measures. The results achieved by the proposed method are suitable for the purpose of clinical treatment and diagnostic support of sickle cell anemia. We present a new method to obtain erythrocyte shape classification using peripheral blood smear sample images. The aim of the method is to segment the cells, to separate clusters and classify cells (circulars, elongated and others). We compared our method with state-of the-art. Results showed that our method with is superior for the diagnosis support of sickle cell anemia.

Vision-based serious games and virtual reality systems for motor rehabilitation: A review geared toward a research methodology.

BACKGROUND: Nowadays, information technologies are being widely adopted to promote healthcare and rehabilitation. Owing to their affordability and use of hand-free controllers, vision-based systems have gradually been integrated into motor rehabilitation programs and have greatly drawn the interest of healthcare practitioners and the research community. Many studies have illustrated the effectiveness of these systems in rehabilitation. However, the report and design aspects of the reported clinical trials were disregarded. OBJECTIVE: In this paper, we present a systematic literature review of the use of vision-based serious games and virtual reality systems in motor rehabilitation programs. We aim to propose a research methodology that engineers can use to improve the designing and reporting processes of their clinical trials. METHODS: We conducted a review of published studies that entail clinical experiments. Searches were performed using Web of Science and Medline (PubMed) electronic databases, and selected studies were assessed using the Downs and Black Checklist and then analyzed according to specific research questions. RESULTS: We identified 86 studies and our findings indicate that the number of studies in this field is increasing, with Korea and USA in the lead. We found that Kinect, EyeToy system, and GestureTek IREX are the most commonly used technologies in studying the effects of vision-based serious games and virtual reality systems on rehabilitation. Findings also suggest that cerebral palsy and stroke patients are the main target groups, with a particular interest on the elderly patients in this target population. The findings indicate that most of the studies focused on postural control and upper extremity exercises and used different measurements during assessment. CONCLUSIONS: Although the research community's interest in this area is growing, many clinical trials lack sufficient clarity in many aspects and are not standardized. Some recommendations have been made throughout the article.

Feasibility of Kinect-Based Games for Balance Rehabilitation: A Case Study.

We aimed at determining the effects of prototype games on older adults attending a rehabilitation program in an elderly house in this work. We conducted an initial case study where two participants underwent a 5-week intervention. Feasibility was assessed by examining recruitment, adherence, and safety. The Tinetti balance test was used as pretest and posttest assessments. Results show that adherence was very high and no adverse effects were registered during the sessions. The included participants also reported enjoyment during the playtime and exhibited improvements in Tinetti scores. The findings suggest that game-based rehabilitation can be useful for improving balance in elderly people and can be incorporated in a fall prevention program.

PROGame: A process framework for serious game development for motor rehabilitation therapy.

Serious game development for rehabilitation therapy is becoming increasingly popular because of the motivational advantages that these types of applications provide. Consequently, the need for a common process framework for this category of software development has become increasingly evident. The goal is to guarantee that products are developed and validated by following a coherent and systematic method that leads to high-quality serious games. This paper introduces a new process framework for the development of serious games for motor rehabilitation therapy. We introduce the new model and demonstrate its application for the development of a serious game for the improvement of the balance and postural control of adults with cerebral palsy. The development of this application has been facilitated by two technological transfer contracts and is being exploited by two different organizations. According to clinical measurements, patients using the application improved from high fall risk to moderate fall risk. We believe that our development strategy can be useful not only for motor rehabilitation therapy, but also for the development of serious games in many other rehabilitation areas.

Métodos computacionales para estudio de la anemia drepanocítica / Study of sickle cell anemia using computacional methods

El procesamiento de imágenes digitales y la visión por computador son ampliamente utilizados en medicina actualmente y son de gran interés las propuestas de nuevos métodos de análisis automatizado de imágenes digitales o mejorar la eficiencia de los existentes. En este trabajo se desarrollaron métodos nuevos para estudiar computacionalmente a través de imágenes de muestras de sangre la drepanocitosis, dolencia con alta incidencia mundial y en Cuba, sobre todo en la región oriental. Se propusieron nuevos métodos de análisis de formas, obtenidos a partir de resultados clásicos de geometría integral y nuevas propuestas de visión por computador para evaluar trastornos neurofisiológicos asociados a través del estudio de las expresiones faciales del paciente. La validación estadística realizada comprobó la superioridad de estos métodos sobre otros, se determinó que son válidos para ser introducidos en software de apoyo para mejorar la calidad de la atención médica(AU)

Digital image processing and computer vision are frequently used in medicine at present and the proposals of new methods of automatic analysis of digital images or the efficiency improvement of the existing are of great interest. In this work new methods to computationally study sickle cell disease through blood samples images are developed, an illness with high incidence in the world and in Cuba, mainly in the eastern region. New shape analysis methods obtained from classical results of integral geometry and new computer vision proposals for evaluate neuro physiological disorders associated with this illness through the study of the facial expressions of the patient were proposed. The statistical validation realized confirmed the superiority of these methods on previous proposals, which is why they are valid to be introduced in support software to improve the quality of the medical attention(AU)

Métodos computacionales para estudio de la anemia drepanocítica / Study of sickle cell anemia using computacional methods

El procesamiento de imágenes digitales y la visión por computador son ampliamente utilizados en medicina actualmente y son de gran interés las propuestas de nuevos métodos de análisis automatizado de imágenes digitales o mejorar la eficiencia de los existentes. En este trabajo se desarrollaron métodos nuevos para estudiar computacionalmente a través de imágenes de muestras de sangre la drepanocitosis, dolencia con alta incidencia mundial y en Cuba, sobre todo en la región oriental. Se propusieron nuevos métodos de análisis de formas, obtenidos a partir de resultados clásicos de geometría integral y nuevas propuestas de visión por computador para evaluar trastornos neurofisiológicos asociados a través del estudio de las expresiones faciales del paciente. La validación estadística realizada comprobó la superioridad de estos métodos sobre otros, se determinó que son válidos para ser introducidos en software de apoyo para mejorar la calidad de la atención médica(AU)

Digital image processing and computer vision are frequently used in medicine at present and the proposals of new methods of automatic analysis of digital images or the efficiency improvement of the existing are of great interest. In this work new methods to computationally study sickle cell disease through blood samples images are developed, an illness with high incidence in the world and in Cuba, mainly in the eastern region. New shape analysis methods obtained from classical results of integral geometry and new computer vision proposals for evaluate neuro physiological disorders associated with this illness through the study of the facial expressions of the patient were proposed. The statistical validation realized confirmed the superiority of these methods on previous proposals, which is why they are valid to be introduced in support software to improve the quality of the medical attention(AU)

Clasificación de eritrocitos empleando modelos ocultos de Márkov / Red Blood cell classification with hidden Markov models

Se realiza un estudio del desempeño de los modelos ocultos de Márkov (HMM) en la clasificación morfológica supervisada de eritrocitos en muestras de sangre periférica de pacientes con anemia drepanocítica. Los contornos se representan de forma novedosa considerando las diferencias angulares en la curvatura de los puntos del mismo. El entrenamiento de cada modelo se realiza tanto con la descripción normal de los contornos como con la representación de la rotación de los mismos, para garantizar una mayor estabilidad en los parámetros estimados. Se desarrolla un proceso de validación cruzada de 5x1 para estimación del error. Se obtienen las medidas de sensibilidad, precisión y especificidad de la clasificación. Los mejores resultados en cuanto a sensibilidad se obtienen al clasificar eritrocitos pertenecientes a dos clases: normales (96 por ciento) y elongados (99 por ciento). Al considerar además una clase de eritrocitos con otras deformaciones los mejores resultados se obtienen realizando el entrenamiento de los modelos con la rotación de todos los contornos, que alcanzó sensibilidades de normales (94 por ciento), elongados (82 por ciento) y con otras deformaciones (76 por ciento)(AU)

A study of the performance of Hidden Markov Models (HMM) in morphologic supervised classification of erythrocytes in peripheral blood smears of patients with sickle cell disease is realized. Contours are represented in original way considering the angular differences in the curvature of the points of the same. The training of every model comes true with the normal description of the contours and with the representation of the rotation of the same, in order to guarantee a bigger stability in the esteemed parameters. A process of validation crossed of 5x1 for estimate of the error is developed. The measures of sensibility, precision and specificity of classification are obtained. The best results obtain when classifying erythrocytes in two classes, with sensibility values in normal of 96 percent and elongated 99 percent. In the classification of erythrocytes considering the class of other deformations better results obtain accomplishing the training of the models with the rotation of all the contours, that it attained sensibilities of normal (94 percent), elongated (82 percent) and with other deformations (76 percent)(AU)

Clasificación de eritrocitos empleando modelos ocultos de Márkov / Red Blood cell classification with hidden Markov models

Se realiza un estudio del desempeño de los modelos ocultos de Márkov (HMM) en la clasificación morfológica supervisada de eritrocitos en muestras de sangre periférica de pacientes con anemia drepanocítica. Los contornos se representan de forma novedosa considerando las diferencias angulares en la curvatura de los puntos del mismo. El entrenamiento de cada modelo se realiza tanto con la descripción normal de los contornos como con la representación de la rotación de los mismos, para garantizar una mayor estabilidad en los parámetros estimados. Se desarrolla un proceso de validación cruzada de 5x1 para estimación del error. Se obtienen las medidas de sensibilidad, precisión y especificidad de la clasificación. Los mejores resultados en cuanto a sensibilidad se obtienen al clasificar eritrocitos pertenecientes a dos clases: normales (96 por ciento) y elongados (99 por ciento). Al considerar además una clase de eritrocitos con otras deformaciones los mejores resultados se obtienen realizando el entrenamiento de los modelos con la rotación de todos los contornos, que alcanzó sensibilidades de normales (94 por ciento), elongados (82 por ciento) y con otras deformaciones (76 por ciento)(AU)

A study of the performance of Hidden Markov Models (HMM) in morphologic supervised classification of erythrocytes in peripheral blood smears of patients with sickle cell disease is realized. Contours are represented in original way considering the angular differences in the curvature of the points of the same. The training of every model comes true with the normal description of the contours and with the representation of the rotation of the same, in order to guarantee a bigger stability in the esteemed parameters. A process of validation crossed of 5x1 for estimate of the error is developed. The measures of sensibility, precision and specificity of classification are obtained. The best results obtain when classifying erythrocytes in two classes, with sensibility values in normal of 96 percent and elongated 99 percent. In the classification of erythrocytes considering the class of other deformations better results obtain accomplishing the training of the models with the rotation of all the contours, that it attained sensibilities of normal (94 percent), elongated (82 percent) and with other deformations (76 percent)(AU)

Red blood cell cluster separation from digital images for use in sickle cell disease.

The study of cell morphology is an important aspect of the diagnosis of some diseases, such as sickle cell disease, because red blood cell deformation is caused by these diseases. Due to the elongated shape of the erythrocyte, ellipse adjustment and concave point detection are applied widely to images of peripheral blood samples, including during the detection of cells that are partially occluded in the clusters generated by the sample preparation process. In the present study, we propose a method for the analysis of the shape of erythrocytes in peripheral blood smear samples of sickle cell disease, which uses ellipse adjustments and a new algorithm for detecting notable points. Furthermore, we apply a set of constraints that allow the elimination of significant image preprocessing steps proposed in previous studies. We used three types of images to validate our method: artificial images, which were automatically generated in a random manner using a computer code; real images from peripheral blood smear sample images that contained normal and elongated erythrocytes; and synthetic images generated from real isolated cells. Using the proposed method, the efficiency of detecting the two types of objects in the three image types exceeded 99.00%, 98.00%, and 99.35%, respectively. These efficiency levels were superior to the results obtained with previously proposed methods using the same database, which is available at http://erythrocytesidb.uib.es/. This method can be extended to clusters of several cells and it requires no user inputs.

Improving vision-based motor rehabilitation interactive systems for users with disabilities using mirror feedback.

Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror) with two different groups of users (8 with disabilities and 32 without disabilities) using usability measures (time-to-start (T(s)) and time-to-complete (T(c))). A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user's own visual feedback (T(s) = 7.09 (P < 0.001) and T(c) = 4.48 (P < 0.005)). In vision-based interaction systems, the input device is the user's own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems.

Interactive rehabilitation system for improvement of balance therapies in people with cerebral palsy.

The present study covers a new experimental system, designed to improve the balance and postural control of adults with cerebral palsy. This system is based on a serious game for balance rehabilitation therapy, designed using the prototype development paradigm and features for rehabilitation with serious games: feedback, adaptability, motivational elements, and monitoring. In addition, the employed interaction technology is based on computer vision because motor rehabilitation consists of body movements that can be recorded, and because vision capture technology is noninvasive and can be used for clients who have difficulties in holding physical devices. Previous research has indicated that serious games help to motivate clients in therapy sessions; however, there remains a paucity of clinical evidence involving functionality. We rigorously evaluated the effects of physiotherapy treatment on balance and gait function of adult subjects with cerebral palsy undergoing our experimental system. A 24-week physiotherapy intervention program was conducted with nine adults from a cerebral palsy center who exercised weekly in 20-min sessions. Findings demonstrated a significant increase in balance and gait function scores resulting in indicators of greater independence for our participating adults. Scores improved from 16 to 21 points in a scale of 28, according to the Tinetti Scale for risk of falls, moving from high fall risk to moderate fall risk. Our promising results indicate that our experimental system is feasible for balance rehabilitation therapy.