503 research outputs found

    Automating the decision making process of Todd’s age estimation method from the pubic symphysis with explainable machine learning

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    Age estimation is a fundamental task in forensic anthropology for both the living and the dead. The procedure consists of analyzing properties such as appearance, ossification patterns, and morphology in different skeletonized remains. The pubic symphysis is extensively used to assess adults’ age-at-death due to its reliability. Nevertheless, most methods currently used for skeleton-based age estimation are carried out manually, even though their automation has the potential to lead to a considerable improvement in terms of economic resources, effectiveness, and execution time. In particular, explainable machine learning emerges as a promising means of addressing this challenge by engaging forensic experts to refine and audit the extracted knowledge and discover unknown patterns hidden in the complex and uncertain available data. In this contribution we address the automation of the decision making process of Todd’s pioneering age assessment method to assist the forensic practitioner in its application. To do so, we make use of the pubic bone data base available at the Physical Anthropology lab of the University of Granada. The machine learning task is significantly complex as it becomes an imbalanced ordinal classification problem with a small sample size and a high dimension. We tackle it with the combination of an ordinal classification method and oversampling techniques through an extensive experimental setup. Two forensic anthropologists refine and validate the derived rule base according to their own expertise and the knowledge available in the area. The resulting automatic system, finally composed of 34 interpretable rules, outperforms the state-of-the-art accuracy. In addition, and more importantly, it allows the forensic experts to uncover novel and interesting insights about how Todd’s method works, in particular, and the guidelines to estimate age-at-death from pubic symphysis characteristics, generally.Ministry of Science and Innovation, Spain (MICINN) Spanish GovernmentAgencia Estatal de Investigacion (AEI) PID2021-122916NB-I00 Spanish Government PGC2018-101216-B-I00Junta de AndaluciaUniversity of Granada P18 -FR -4262 B-TIC-456-UGR20European CommissionUniversidad de Granada/CBU

    THREE-DIMENSIONAL GEOMETRIC MORPHOMETRIC SEX DETERMINATION AND MODELED FRAGMENTARY ANALYSIS OF THE HUMAN PUBIC BONE

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    Geometric morphometrics has become a more popular method in anthropology as three-dimensional data and research become more widely recognized and accessible. This research provides a refined method utilizing 3-D geometric morphometric analysis to determine sex from the human pubic bone. The study used a sample of N=378 individual pubic bones from the University of New Mexico Maxwell Documented Collection. Eight landmarks were digitized on each individual bone using a Microscribe Digitizer. Results from the Principal Components Analysis provide promising clustering between male and female groups, as well as indications that the method may be ancestry-specific, and that parity may have an effect on the shape of female pubic bones. The Discriminant Function analysis of the training data set resulted in 96.2% accuracy in predicting the correct sex, and the testing data set resulted in 95.5% accuracy, P\u3c0.0001. To test the ability to replicate this method, the author collected data a second time on a random set of 50 individuals, N=100 pubic bones and reran the GPA, PCA, and discriminant function analyses. This second test resulted in 96.5% accuracy of the training data set, and 93.8% accuracy of the testing data set. To test interobserver error, the author collected all eight landmarks from the same bone once a day, six days in a row. The PCA scatter plot of this test is presented to exhibit the extremely low variance between each instance of measurement. In order to make this method more applicable to real casework, a modeled fragmentary analysis was also conducted. Statistical analyses and machine learning algorithms were used to mimic fragmented remains that included tests run on each possible landmark combination of three or more landmarks to simulate fragmented bones (218 combinations). The results of the modeled fragmentary analysis consisted of 133 combinations which exhibit a 90% or higher accuracy in sex prediction; and nine combinations which exhibit 95.5% accuracy in sex prediction. In particular, three landmarks clustered around the ventral arc of the pubic bone performed the best, indicating this is the most sexually dimorphic portion of the bone. These results indicate that three-dimensional geometric morphometrics is a valid method to be applied to sex determination in forensic anthropology

    A Survey on Artificial Intelligence Techniques for Biomedical Image Analysis in Skeleton-Based Forensic Human Identification

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    This paper represents the first survey on the application of AI techniques for the analysis of biomedical images with forensic human identification purposes. Human identification is of great relevance in today’s society and, in particular, in medico-legal contexts. As consequence, all technological advances that are introduced in this field can contribute to the increasing necessity for accurate and robust tools that allow for establishing and verifying human identity. We first describe the importance and applicability of forensic anthropology in many identification scenarios. Later, we present the main trends related to the application of computer vision, machine learning and soft computing techniques to the estimation of the biological profile, the identification through comparative radiography and craniofacial superimposition, traumatism and pathology analysis, as well as facial reconstruction. The potentialities and limitations of the employed approaches are described, and we conclude with a discussion about methodological issues and future research.Spanish Ministry of Science, Innovation and UniversitiesEuropean Union (EU) PGC2018-101216-B-I00Regional Government of Andalusia under grant EXAISFI P18-FR-4262Instituto de Salud Carlos IIIEuropean Union (EU) DTS18/00136European Commission H2020-MSCA-IF-2016 through the Skeleton-ID Marie Curie Individual Fellowship 746592Spanish Ministry of Science, Innovation and Universities-CDTI, Neotec program 2019 EXP-00122609/SNEO-20191236European Union (EU)Xunta de Galicia ED431G 2019/01European Union (EU) RTI2018-095894-B-I0

    Radiographic assessment of the pubic symphysis in elite male adolescent football players:Development and reliability of the Maturing Adolescent Pubic Symphysis (MAPS) classification

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    Introduction: The pubic symphysis is susceptible to growth related injuries long after the adolescent growth spurt. Our study describes the radiographic maturation of the pubic symphysis on pelvic radiographs in adolescent football players and introduces the Maturing Adolescent Pubic Symphysis classification (MAPS classification). Methods: Anteroposterior pelvic radiographs of 105 healthy adolescent male football players between 12 and 24 years old were used to develop the classification system. The radiological scoring of the symphyseal joint was developed over five rounds. The final MAPS classification items were scored in random order by two experienced readers, blinded to the age of the participant and to each other's scoring. The inter- and intra-rater reliability were examined using weighted kappa (κ). Results: We developed a classification system with descriptive definitions and an accompanying pictorial atlas. The symphyseal joint was divided into three regions: the superior corners, and the upper and lower regions of the joint line. Inter-rater reliability was substantial to almost perfect: superior region: κ = 0.70 (95% CI 0.60–––0.79), upper region of the joint line: κ = 0.89 (95% CI 0.86–––0.92), lower region of the joint line: κ = 0.65 (95% CI 0.55–––0.75). The intra-observer reliability showed similar results. Conclusion: The Maturing Adolescent Pubic Symphysis classification (MAPS classification) is a reliable descriptive classification of the radiographic maturation of the pubic symphysis joint in athletic males. The stages can provide a basis for understanding in clinical practice and will allow future research in this field.</p

    Odhad věku dožití dospělého jedince podle kostry: Nové přístupy hodnocení indikátorů senescence

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    Odhad věku dožití dospělých jedinců je stále velmi problematická součást odhadu biologického profilu jedince. Současné metody odhadu věku jsou schopné věk odhadovat přesně a spolehlivě pouze ve velmi širokých věkových rozmezích. Ke zlepšení této situace nepřispívá ani fakt, že jsou tyto postupy založeny většinou jen na užití jednoho kosterního indikátoru, ať jsou věkové změny hodnoceny vizuálně, či se opírají o nevhodné statistické přístupy. Disertační projekt vychází z těchto nedostatků a jeho cílem je přispět k lepšímu porozumění problematiky a především do výzkumu začlenit a otestovat nové technologie a výpočetní přístupy. Charakter disertační práce je spíše metodologický a celý výzkum byl rozdělen na tři oddělené části, čemuž odpovídá i stanovení tří hlavních cílů. Prvním cílem bylo aplikovat v multi-populačním souboru vizuálně hodnocených dat (n=941) dvou artikulačních plošek pánevní kosti různé sofistikované matematické postupy s cílem dosáhnout přesnějšího odhadu věku dožití. Výsledné hodnoty RMSE, které byly v rozmezí 12 až 14 let však o zpřesnění odhadu nevypovídají. Dále jsme se zaměřili na zhodnocení výstupů z různých skenovacích zařízení a vlivu případných odchylek v zachycení povrchu kloubní plochy pubické symfýzy na analýzy odhadu věku. Soubor 29 pánevních kostí české středověké...Age-at-death estimation of adults is still a very difficult part of estimation of individual's biological profile. Current age estimation methods can estimate age accurately and reliably only as very broad age ranges. The fact that these approaches are mostly based on only one skeletal indicator, whose age changes are assessed visually, or are based on an inappropriate statistical approach, does not contribute to the improvement of this situation. The dissertation project is based on these shortcomings and it aims to contribute to a better understanding of the issue and to integrate and test new technologies and computational approaches in research. Given the methodological nature of this dissertation, the whole research was divided into three separate parts, which corresponds to the establishment of three main objectives. The first objective was to apply different sophisticated mathematical techniques in a multi-population database of visually evaluated data (n=941) of two articulation surfaces of os coxae to achieve a more accurate estimate of age. However, the resulting RMSE, which ranged between 12 to 14 years, do not indicate an accurate estimate. Furthermore, we focused on the evaluation of outputs from various scanning devices and we tested the influence of possible differences in captured...Department of Anthropology and Human GeneticsKatedra antropologie a genetiky člověkaFaculty of SciencePřírodovědecká fakult

    A case of erosive polyarthropathy from Medieval northern Italy (12th–13th centuries)

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    Objective: To evaluate and differentially diagnose erosive skeletal lesions located on multiple joints of an individual archaeologically recovered in 2017. Materials: Skeletal remains of a well-preserved skeleton dating to the 12th–13th centuries from the Medieval church of San Biagio in Cittiglio (Varese, northern Italy). Methods: Macroscopic and radiographic imaging. Results: Erosive marginal symmetrical lesions are present on the metatarsophalangeal, metacarpophalangeal and interphalangeal joints of an adult male, aged 55–75 years. Osteolytic changes, in the form of pocket erosions, surface resorptions and pseudocyst formations, are also macroscopically observed on some carpal and tarsal bones and on several large peripheral joints. Conclusions: A careful differential diagnosis of the lesions and their macroscopic and radiological appearance are suggestive of a case of rheumatoid arthritis-like polyarthropathy. Significance: This case contributes to the debate regarding the antiquity of erosive polyarthropathies, providing additional evidence for the existence of these diseases in the Old World prior to the discovery of the Americas. Limitations: Small sample size limits discussion of the scope of the disease in antiquity. Suggestions for further research: This case highlights the need for further macroscopic, radiographic, and biomolecular studies of pre-modern European skeletal samples to investigate the hypothesized pre-existence of these pathological conditions in Europe prior to 1492

    Segmentation of pelvic structures from preoperative images for surgical planning and guidance

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    Prostate cancer is one of the most frequently diagnosed malignancies globally and the second leading cause of cancer-related mortality in males in the developed world. In recent decades, many techniques have been proposed for prostate cancer diagnosis and treatment. With the development of imaging technologies such as CT and MRI, image-guided procedures have become increasingly important as a means to improve clinical outcomes. Analysis of the preoperative images and construction of 3D models prior to treatment would help doctors to better localize and visualize the structures of interest, plan the procedure, diagnose disease and guide the surgery or therapy. This requires efficient and robust medical image analysis and segmentation technologies to be developed. The thesis mainly focuses on the development of segmentation techniques in pelvic MRI for image-guided robotic-assisted laparoscopic radical prostatectomy and external-beam radiation therapy. A fully automated multi-atlas framework is proposed for bony pelvis segmentation in MRI, using the guidance of MRI AE-SDM. With the guidance of the AE-SDM, a multi-atlas segmentation algorithm is used to delineate the bony pelvis in a new \ac{MRI} where there is no CT available. The proposed technique outperforms state-of-the-art algorithms for MRI bony pelvis segmentation. With the SDM of pelvis and its segmented surface, an accurate 3D pelvimetry system is designed and implemented to measure a comprehensive set of pelvic geometric parameters for the examination of the relationship between these parameters and the difficulty of robotic-assisted laparoscopic radical prostatectomy. This system can be used in both manual and automated manner with a user-friendly interface. A fully automated and robust multi-atlas based segmentation has also been developed to delineate the prostate in diagnostic MR scans, which have large variation in both intensity and shape of prostate. Two image analysis techniques are proposed, including patch-based label fusion with local appearance-specific atlases and multi-atlas propagation via a manifold graph on a database of both labeled and unlabeled images when limited labeled atlases are available. The proposed techniques can achieve more robust and accurate segmentation results than other multi-atlas based methods. The seminal vesicles are also an interesting structure for therapy planning, particularly for external-beam radiation therapy. As existing methods fail for the very onerous task of segmenting the seminal vesicles, a multi-atlas learning framework via random decision forests with graph cuts refinement has further been proposed to solve this difficult problem. Motivated by the performance of this technique, I further extend the multi-atlas learning to segment the prostate fully automatically using multispectral (T1 and T2-weighted) MR images via hybrid \ac{RF} classifiers and a multi-image graph cuts technique. The proposed method compares favorably to the previously proposed multi-atlas based prostate segmentation. The work in this thesis covers different techniques for pelvic image segmentation in MRI. These techniques have been continually developed and refined, and their application to different specific problems shows ever more promising results.Open Acces

    The Skeletal Biology of the Caddo Indians of the Kaufman-Williams Site, Red River County, Texas

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    A comprehensive biological analysis of the skeletal remains from the Kaufman-Williams site, 41RR16, Red River County, Texas, was conducted. The primary purpose of the investigation was to expand our knowledge about the biological variability found among the prehistoric Caddo. Cranial and postcranial measurements were taken, and indices were calculated. Several non-metrical characters were observed. The health status of the group was assessed based upon the pathological conditions noted in the bones. Cranial deformation was studied in detail, particularly its effect on craniofacial measurements. A further analysis attempted to relate the skeletal material from the Kaufman-Williams site to Caddoan skeletal samples discussed in Maples (1962) and Westbury (1978) and to skeletal samples from the Saint Helena phase in Nebraska and from the Mobridge and Rygh sites (Arikara) in South Dakota. All of these groups were members of the Caddoan Linguistic Family. The Penrose Size and Shape Coefficient was used in the analysis since only literature data was available for the Caddo studies. Seventy-five skeletons were used in the biological analysis. They were dug by Gregory Perino of the Museum of the Red River, Idabel, Oklahoma. The skeletal material was given to Dr. William M. Bass, University of Tennessee, Knoxville, Tennessee, who made them available to the author. There were 28 females, 26 males, and 21 subadults in the sample. The two health conditions which probably caused the greatest problem for the inhabitants of the site were dental caries and abscesses and degenerative arthritis. Congenital defects, which probably caused no problems, occurred quite frequently. Twenty-eight percent of the deaths occurred among subadults. The highest death rate for males occurred between 30. 0 and 34. 9 years of age. The females had two periods of high death rate--one between 30.0 and 34. 9 years of age and the other between 45. 0 and 49. 9. The skulls from Kaufman-Williams were almost all intentionally cranially deformed. Parallelo-fronto-occipital deformation was the most common type. Two ratios (Frontal Deformation Ratio and Occipital Deformation Ratio) were devised to quantify the amount of deformation observed. The skulls were then grouped into deformation classes based upon these ratios. The three-cluster arrangement of the skulls based on the deformation ratios agreed well with the author\u27s subjective classification. However, small cluster groups necessitated realignment of the skulls into two groups--moderate and extreme--for later comparisons. Three tests, based upon either the two deformation ratios or upon the two deformation classes, were conducted to determine which craniofacial measurements were affected by deformation. These tests showed that, in general, breadth measurements were most affected by deformation. Those measurements which seemed to be most significantly affected by deformation were not used in the Penrose Size and Shape calculation. The Penrose distance calculation placed the Cooper Lake material (Westbury 1978) generally more distant from the other populations; however, among the females Cooper Lake and Sanders (Maples 1962) were close. The Penrose coefficient placed the Kaufman-Williams, Arikara, and Saint Helena morphologically close. The discrete trait analysis showed no significant sex, bilateral, or deformation class differences in the frequency of the traits. However, there were several traits which occurred in higher frequencies in both sexes in either the moderate or extreme deformation classes. This study broadens our knowledge about the Caddo Indians and about their placement within the Caddoan Linguistic Family; however, many more such studies need to be completed. Furthermore, comparison of the Caddo with other nearby groups in the Texas-Oklahoma area should be conducted

    Ancestry-independent osteometric sex estimation from selected postcranial skeletal elements of South Africans: a machine learning approach

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    Sex estimation, as part of a biological profile, has the power to halve the number of possible identities of unidentified skeletal remains. Postcranial elements have been studied in South Africa (SA) for the purpose of sex estimation and have often proven to be more accurate than the cranium. Estimation techniques using postcranial elements in SA almost exclusively utilise discriminant analysis to evaluate sex, but international publications have shown success using alternative machine learning (ML) algorithms. SA methods and standards are often restricted by limited sample size, lack of robust statistical techniques in older publications and, the prerequisite of known or estimated ancestry. Most methods are specific to SA African, European or, more recently, Mixed ancestry groups and are unreliable when ancestry is unknown. The aim of this study was to apply a series of ML algorithms to train ancestry independent sex classification models using postcranial osteometric measurements from the cadaveric skeletal remains of modern South Africans, focussing on long bone joints. The study consisted of a roughly demographically representative, pooled sample, of 650 South Africans (325 male, 325 female). 12 osteometric measurements were taken from available left- and, or right-sided bones for each individual. All 12 mensurations were sexually dimorphic and differences between left- and right-sided bones were negligible. The dataset was subjected to ML algorithm training using univariate and multivariate predictor combinations. The best performing ML algorithm, given the sample size and available predictors was discriminant function analysis. Univariate model accuracies ranged from 80.5-89.1% and multivariate model accuracies ranged from 84.5%, using 2 predictors, to 92.8%, using 12 predictors. An optimised 3-predictor model was able to predict sex with 92.7% accuracy. Results from this study were comparable to those using ancestry-specific models and non-ancestry-specific models, where available. Findings from this study suggest that the inclusion of ancestry, when predicting sex using the elements examined, is not necessary as it does not significantly improve prediction accuracy
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