Deep-Learning-Based Computer- Aided Systems for Breast Cancer Imaging: A Critical Review

[EN] This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis/detection (CAD) systems, which make use of new deep learning methods to automatically recognize breast images and improve the accuracy of diagnoses made by radiologists. This review is based upon published literature in the past decade (January 2010-January 2020), where we obtained around 250 research articles, and after an eligibility process, 59 articles were presented in more detail. The main findings in the classification process revealed that new DL-CAD methods are useful and effective screening tools for breast cancer, thus reducing the need for manual feature extraction. The breast tumor research community can utilize this survey as a basis for their current and future studies.This project has been co-financed by the Spanish Government Grant PID2019-107790RB-C22, "Software development for a continuous PET crystal systems applied to breast cancer".Jiménez-Gaona, Y.; Rodríguez Álvarez, MJ.; Lakshminarayanan, V. (2020). Deep-Learning-Based Computer- Aided Systems for Breast Cancer Imaging: A Critical Review. Applied Sciences. 10(22):1-29. https://doi.org/10.3390/app10228298S1291022Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61(2), 69-90. doi:10.3322/caac.20107Gao, F., Chia, K.-S., Ng, F.-C., Ng, E.-H., & Machin, D. (2002). Interval cancers following breast cancer screening in Singaporean women. International Journal of Cancer, 101(5), 475-479. doi:10.1002/ijc.10636Munir, K., Elahi, H., Ayub, A., Frezza, F., & Rizzi, A. (2019). 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In the development of the learning process, the teacher must find the best way for students to acquire new knowledge by applying strategies to improve education and academic quality by applying innovative learning and evaluation methodologies. The objective of this research is to implement strategies based on gamification for learning matrix algebra in engineering students at the Universidad Técnica Particular de Loja. The methodology was of quasi-experimental design, with a population of 50 first-cycle students of the Environmental Management and Business Administration careers, forming the control and experimental groups, respectively. Gamification was applied to the experimental group and traditional teaching was applied to the control group.En el desarrollo del proceso de aprendizaje, el docente debe buscar la mejor manera para que los estudiantes adquieran nuevos conocimientos mediante la aplicación de estrategias de mejoramiento de la educación y de la calidad académica aplicando metodologías innovadoras de aprendizaje y evaluación. Esta investigación tiene como objetivo implementar estrategias basadas en gamificación para el aprendizaje del álgebra matricial en los estudiantes de Ingeniería de la Universidad Técnica Particular de Loja. La metodología fue de diseño cuasi-experimental, con una población de 50 estudiantes de primer ciclo de las carreras Gestión Ambiental y Administración de Empresas, conformando los grupos control y experimental respectivamente. Al grupo experimental que se le aplicó gamificación y al grupo control la enseñanza tradicional

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The multidisciplinary Hackathon academic activity was applied to some groups of mathematics in Universidad Técnica Particular de Loja students during the period time of in October 2016 - March 2017. The students registered worked in multidisciplinary groups to try to response: What problem or social necessity has been detected and how do you resolve? The academic activity was develop in three phases, informative, assay and evaluation. The application of design thinking methodology allow to porpoise the solution in different challenges in environment, food, technologic and educative. A commission stablished evaluated according to a rubric the best project. The results show that the students know and applies the new learning methodologies to learn and apply in future project in science, medicine, education and biotechnology. Keywords: La actividad académica Hackathon multidisciplinario fue aplicada a diferentes grupos de estudiantes de varios componentes de matemáticas de la Universidad Técnica Particular de Loja en el semestre octubre 2016 – marzo 2017. Los estudiantes inscritos a la actividad formaron grupos multidisciplinarios, generando propuestas a la pregunta: ¿Qué problema o necesidad social has detectado y te gustaría resolver? La actividad académica se ejecutó en 3 etapas informativas, de ensayo y evaluación. A través de la aplicación de la metodología Desing thinking los grupos de trabajo diseñaron posibles soluciones a los retos planteados. Estas soluciones fueron definidas en el ámbito tecnológico, alimentario, ambiental, farmacológico y educativo. La comisión de docentes eligió la mejor solución en base a la rúbrica de evaluación, y posteriormente, se realizó una retroalimentación a cada una de las propuestas. Los resultados obtenidos de este proyecto muestran que el estudiante conoce y aplica el uso de nuevas metodologías de aprendizaje para ser adaptadas en futuros proyectos en ciencia, medicina, educación y biotecnología

Aprendizaje de la matemática basado en el contexto de las ciencias: Mathematics learning based on the science context

This teaching innovation work aims to promote understanding on fundamental mathematics topics such as equations and functions, through the related sciences contextualization. In addition to strengthening the reflective and intuitive thinking ability, for the context problems resolution through different strategies.The methodology, contextual learning theory REACT was addressed; in four stages: Master class, Case studies design, Cases application in the classroom, Contextual learning evaluation and monitoring. Among the most relevant results, it can be mentioned that 90% increased their interest by the mathematics study. In conclusion, the contextual learning method provides the student with a stronger academic base and facilitates the mathematical concepts understanding that relate to their professional environment.Este trabajo de innovación docente tiene como propósito promover la comprensión sobre temas fundamentales de matemática como ecuaciones y funciones, mediante la contextualización de ciencias afines. Además de fortalecer la capacidad de pensamiento reflexivo e intuitivo, para la resolución de problemas de contexto mediante diferentes estrategias. Se abordó la metodología, teoría del aprendizaje contextual REACT; en cuatro etapas: Clase magistral, Diseño de casos de estudios, Aplicación de los casos en el aula, Seguimiento y evaluación del aprendizaje contextual. Dentro de los resultados más relevantes se pueden mencionar que el 90% incrementó su interés por el estudio de la matemática. En conclusión, el método de aprendizaje contextual le proporciona al alumno una base académica más fuerte y facilita la comprensión de conceptos matemáticos que se relacionan con su entorno profesional. &nbsp

El Aprendizaje Basado en Proyectos y su aplicación didáctica en la enseñanza de las medidas de localización

In recent years, there have been many difficulties in the teaching-learning of mathematics, before this arises the need to seek innovative teaching-learning practices that place the student at the center of the educational process. Project-Based Learning (PBL) is an active methodology that facilitates teacher-student interaction and achieves significant learning. The objective of this work is to determine the incidence of PBL and its application in location measures at the basic level. The applied methodology describes an exploratory-descriptive quantitative investigation. The results indicate a considerable difference before and after the application of the ABP.En los últimos años se han evidenciado muchas dificultades en la enseñanza-aprendizaje de la matemática, ante ello surge la necesidad de buscar prácticas innovadoras de enseñanza-aprendizaje que ubiquen al estudiante en el centro del proceso educativo. El Aprendizaje Basado en Proyectos (ABP) es una metodología activa que facilita la interacción docente-estudiante y consigue aprendizajes significativos. El objetivo de este trabajo es determinar la incidencia del ABP y su aplicación en las medidas de localización a nivel básico. La metodología aplicada describe una investigación cuantitativa de tipo exploratorio-descriptivo. Los resultados indican una diferencia considerable antes y después de la aplicación del ABP.&nbsp

Deep-Learning-Based Computer-Aided Systems for Breast Cancer Imaging: A Critical Review

This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis/detection (CAD) systems, which make use of new deep learning methods to automatically recognize breast images and improve the accuracy of diagnoses made by radiologists. This review is based upon published literature in the past decade (January 2010–January 2020), where we obtained around 250 research articles, and after an eligibility process, 59 articles were presented in more detail. The main findings in the classification process revealed that new DL-CAD methods are useful and effective screening tools for breast cancer, thus reducing the need for manual feature extraction. The breast tumor research community can utilize this survey as a basis for their current and future studies

Radiomics Diagnostic Tool Based on Deep Learning for Colposcopy Image Classification

Background: Colposcopy imaging is widely used to diagnose, treat and follow-up on premalignant and malignant lesions in the vulva, vagina, and cervix. Thus, deep learning algorithms are being used widely in cervical cancer diagnosis tools. In this study, we developed and preliminarily validated a model based on the Unet network plus SVM to classify cervical lesions on colposcopy images. Methodology: Two sets of images were used: the Intel & Mobile ODT Cervical Cancer Screening public dataset, and a private dataset from a public hospital in Ecuador during a routine colposcopy, after the application of acetic acid and lugol. For the latter, the corresponding clinical information was collected, specifically cytology on the PAP smear and the screening of human papillomavirus testing, prior to colposcopy. The lesions of the cervix or regions of interest were segmented and classified by the Unet and the SVM model, respectively. Results: The CAD system was evaluated for the ability to predict the risk of cervical cancer. The lesion segmentation metric results indicate a DICE of 50%, a precision of 65%, and an accuracy of 80%. The classification results’ sensitivity, specificity, and accuracy were 70%, 48.8%, and 58%, respectively. Randomly, 20 images were selected and sent to 13 expert colposcopists for a statistical comparison between visual evaluation experts and the CAD tool (p-value of 0.597). Conclusion: The CAD system needs to improve but could be acceptable in an environment where women have limited access to clinicians for the diagnosis, follow-up, and treatment of cervical cancer; better performance is possible through the exploration of other deep learning methods with larger datasets

La biomatemática y su aplicación en proyectos biotecnológicos

Proyecto presentado por la Universidad Técnica Particular de Loja para participar por el "Premio Latinoamericano a la Innovación en Educación Superior 2021". La aplicación de la matemática y la biotecnología han encontrado puntos de apoyo como, por ejemplo, el estudio del crecimiento poblacional; biorremediación, mejora de la producción, seguridad alimentaria, biocombustibles entre otros. En este sentido, es imprescindible considerar que durante la formación académica el estudiante debe conocer y ser consciente de la importancia de las matemáticas y su aplicabilidad en su perfil profesional. Así que, mediante la metodología Aprendizaje Basado en Proyectos se generaron soluciones matemáticas a bioemprendimientos dentro de las categorías de agroalimentación y medio ambiente. Como resultado de esta experiencia formativa el docente mejora la didáctica de la matemática e incrementa el porcentaje de aprobación del curso, mientras que el alumno incrementa su grado de motivación por el estudio de esta ciencia. Se concluye que la enseñanza de las ciencias, de forma particular la matemática debe estar orientada a desarrollar competencias, destrezas y habilidades que permitan a los estudiantes generar soluciones y ampliar su visión sobre la aplicabilidad de su carrera

Compensatory Base Changes in ITS2 Secondary Structure Alignment, Modelling, and Molecular Phylogeny: An Integrated Approach to Improve Species Delimitation in <i>Tulasnella</i> (Basidiomycota)

Background: The delimitation of species of Tulasnella has been extensively studied, mainly at the morphological (sexual and asexual states) and molecular levels—showing ambiguity between them. An integrative species concept that includes characteristics such as molecular, ecology, morphology, and other information is crucial for species delimitation in complex groups such as Tulasnella. Objectives: The aim of this study is to test evolutionary relationships using a combination of alignment-based and alignment-free distance matrices as an alternative molecular tool to traditional methods, and to consider the secondary structures and CBCs from ITS2 (internal transcribed spacer) sequences for species delimitation in Tulasnella. Methodology: Three phylogenetic approaches were plotted: (i) alignment-based, (ii) alignment-free, and (iii) a combination of both distance matrices using the DISTATIS and pvclust libraries from an R package. Finally, the secondary structure consensus was modeled by Mfold, and a CBC analysis was obtained to complement the species delimitation using 4Sale. Results and Conclusions: The phylogenetic tree results showed delimited monophyletic clades in Tulasnella spp., where all 142 Tulasnella sequences were divided into two main clades A and B and assigned to seven species (T. asymmetrica, T. andina, T. eichleriana ECU6, T. eichleriana ECU4 T. pinicola, T. violea), supported by bootstrap values from 72% to 100%. From the 2D secondary structure alignment, three types of consensus models with helices and loops were obtained. Thus, T. albida belongs to type I; T. eichleriana, T. tomaculum, and T. violea belong to type II; and T. asymmetrica, T. andina, T. pinicola, and T. spp. (GER) belong to type III; each type contains four to six domains, with nine CBCs among these that corroborate different species

Radiomics Diagnostic Tool Based on Deep Learning for Colposcopy Image Classification

Background: Colposcopy imaging is widely used to diagnose, treat and follow-up on premalignant and malignant lesions in the vulva, vagina, and cervix. Thus, deep learning algorithms are being used widely in cervical cancer diagnosis tools. In this study, we developed and preliminarily validated a model based on the Unet network plus SVM to classify cervical lesions on colposcopy images. Methodology: Two sets of images were used: the Intel & Mobile ODT Cervical Cancer Screening public dataset, and a private dataset from a public hospital in Ecuador during a routine colposcopy, after the application of acetic acid and lugol. For the latter, the corresponding clinical information was collected, specifically cytology on the PAP smear and the screening of human papillomavirus testing, prior to colposcopy. The lesions of the cervix or regions of interest were segmented and classified by the Unet and the SVM model, respectively. Results: The CAD system was evaluated for the ability to predict the risk of cervical cancer. The lesion segmentation metric results indicate a DICE of 50%, a precision of 65%, and an accuracy of 80%. The classification results’ sensitivity, specificity, and accuracy were 70%, 48.8%, and 58%, respectively. Randomly, 20 images were selected and sent to 13 expert colposcopists for a statistical comparison between visual evaluation experts and the CAD tool (p-value of 0.597). Conclusion: The CAD system needs to improve but could be acceptable in an environment where women have limited access to clinicians for the diagnosis, follow-up, and treatment of cervical cancer; better performance is possible through the exploration of other deep learning methods with larger datasets