Daniela Mayumi Ushizima

Lawrence Berkeley National Laboratory | LBL · Computational Research Division (CRD)

A análise de células cervicais a partir de exames de Papanicolaou convencionais ainda é um grande desafio. Diferentemente das imagens de exame em meio líquido, a citologia convencional possui muita sobreposição celular e diversas estruturas epiteliais que dificultam a implementação de metodologias computacionais que possam dar suporte à automação d...

Micro-computed tomography (µCT) is a valuable tool for visualizing microstructures and damage in fiber-reinforced composites. However, the large sets of data generated by µCT present a barrier to extracting quantitative information. Deep learning models have shown promise for overcoming this barrier by enabling automated segmentation of features of...

Fiber-reinforced ceramic-matrix composites are advanced, temperature resistant materials with applications in aerospace engineering. Their analysis involves the detection and separation of fibers, embedded in a fiber bed, from an imaged sample. Currently, this is mostly done using semi-supervised techniques. Here, we present an open, automated comp...

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains pro...

Background Imaging methods that are non‐destructive preserve tissue integrity and lead to improved topography analysis for the study of neurodegenerative diseases like Alzheimer’s Disease (AD). Immunofluorescence (IF) staining methods facilitate such investigations by addressing a gradient of intensity variations relevant for in situ cell detection...

Background Imaging methods that are non‐destructive preserve tissue integrity and lead to improved topography analysis for the study of neurodegenerative diseases like Alzheimer’s Disease (AD). Immunofluorescence (IF) staining methods facilitate such investigations by addressing a gradient of intensity variations relevant for in situ cell detection...

The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the early diagnosis and treatment planning for patients with suspected or confirmed COVID-19 infection....

In recent years, deep learning methods have outperformed previous state-of-the-art machine learning techniques for several problems, including image classification. Classifying cells in Pap smear images is very challenging, and it is still of paramount importance for cytopathologists. The Pap test is a cervical cancer prevention test that tracks pr...

The Pap test is a preventive approach that requires specialized and labor-intensive examination of cytological preparations to track potentially cancerous cells from the internal and external cervix surface. A cytopathologist must analyze many microscopic fields while screening for abnormal cells. Therefore there is hope that a support decision sys...

The execution and analysis of complex experiments are challenged by the vast dimensionality of the underlying parameter spaces. Although an increase in data-acquisition rates should allow broader querying of the parameter space, the complexity of experiments and the subtle dependence of the model function on input parameters remains daunting owing...

Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates...

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-re...

This paper presents a novel hierarchical nuclei segmentation algorithm for isolated and overlapping cervical cells based on a narrow band level set implementation. Our method applies a new multiscale analysis algorithm to estimate the number of clusters in each image region containing cells, which turns into the input to a narrow band level set alg...

Fiber-reinforced ceramic-matrix composites are advanced materials resistant to high temperatures, with application to aerospace engineering. Their analysis depends on the detection of embedded fibers, with semi-supervised techniques usually employed to separate fibers within the fiber beds. Here we present an open computational pipeline to detect f...

There is renewed interest in using advanced techniques to characterize ancient Roman concrete due to its exceptional durability and low-carbon footprint. In the present work, samples were drilled from the "Hospitium" in Pompeii and were analyzed by synchrotron microtomography (μCT) and neutron radiography to study how the microstructure, including...

The nuclei and cytoplasm segmentation of cervical cells is a well studied problem. However, the current segmentation algorithms are not robust to clinical practice due to the high computational cost or because they cannot accurately segment cells with high overlapping. In this paper, we propose a method that is capable of segmenting both cytoplasm...

Abstract: The nuclei and cytoplasm segmentation of cervical cells is a well studied problem. However, the current segmentation algorithms are not robust to clinical practice due to the high computational cost or because they cannot accurately segment cells with high overlapping. In this paper, we propose a method that is capable of segmenting both...

Calcium silicate hydrate (C‐S‐H), is the principal hydration product of Portland cement that mainly contributes to the physical and mechanical properties of concrete. This paper aims to investigate the three‐dimensional structure of C‐S‐H with Ca/Si ratios of 1.0 and 1.6 at the nanoscale using electron tomography. The 3D reconstructions and selecte...

There is renewed interest in using advanced techniques to characterize ancient Roman concrete. In the present work, samples were drilled from the "Hospitium" in Pompeii and were analyzed by synchrotron microtomography (uCT) and neutron radiography to study how the microstructure, including the presence of induced cracks, affects their water adsorpt...

Ancient Roman concrete presents exceptional durability, low-carbon footprint, and interlocking minerals that add cohesion to the final composition. Understanding of the structural characteristics of these materials using X-ray tomography (XRT) is of paramount importance in the process of designing future materials with similar complex heterogeneous...

The focus of this work is on the detection of nuclei in synthetic images of cervical cells. Finding nuclei is an important step in building a computational method to help cytopathologists identify cell changes from Pap smears. The method developed in this work combines both the Multi-Start and the Iterated Local Search metaheuristics and uses the f...

Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based computational models and grid resolutions. An ongoing problem in the field is how to simulate these systems faster but...

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefor...

Ceramic matrix composites are resistant materials that withstand high temperatures, but quality control of such composites depends on microtomography image analysis to enable the spatial analysis of fibers, matrix cracks detection, among others. While there are several approaches for fiber detection from microtomography, materials scientists lack c...

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefor...

Background and objectives: Saliency refers to the visual perception quality that makes objects in a scene to stand out from others and attract attention. While computational saliency models can simulate the expert's visual attention, there is little evidence about how these models perform when used to predict the cytopathologist's eye fixations. S...

We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data representation of a molecule. We define multiple channels that describe different spatial resolutions for each atom type that utilizes cropping, pooling, and concatenation to...

This work addresses segmentation of volumetric images of woven carbon fiber textiles from micro‐tomography data. We propose a semi‐supervised algorithm to classify carbon fibers that requires sparse input as opposed to completely labeled images. The main contributions are: (a) design of effective discriminative classifiers, for three‐dimensional te...

We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data representation of a molecule. We define multiple channels that describe different spatial resolutions for each atom type that utilizes cropping, pooling, and concatenation to...

This paper introduces computational tools for cell classification into normal and abnormal, as well as content-based-image-retrieval (CBIR) for cell recommendation. It also proposes the radial feature descriptors (RFD), which define evenly interspaced segments around the nucleus, and proportional to the convexity of the nuclear boundary. Experiment...

Computer vision for the characterization of fibers in material design

This paper describes our automatic cell image classification algorithm that explores expert’s eye tracking data combined to convolutional neural networks. Our framework selects regions of interest that attract cytologists attention, then it focuses computation on cell classification of these specific sub-images. Our contribution is to fuse deep lea...

Nano-structured thin films have a variety of applications from waveguides, gaseous sensors to piezoelectric devices. Grazing Incidence Small Angle x-ray Scattering images enable classification of such materials. One challenge is to determine structure information from scattering patterns alone. This paper highlights the design of multiple Convoluti...

Ninety years after its invention, the Pap test continues to be the most used method for the early identification of cervical precancerous lesions. In this test, the cytopathologists look for microscopic abnormalities in and around the cells, which is a time-consuming and prone to human error task. This paper introduces computational tools for cytol...

This book constitutes the refereed proceedings of the 14th International Symposium on Visual Computing, ISVC 2019, held in Lake Tahoe, NV, USA in October 2019. The 100 papers presented in this double volume were carefully reviewed and selected from 163 submissions. The papers are organized into the following topical sections: Deep Learning I; Compu...

The explosion in the rate, quality and diversity of image acquisition instruments has propelled the development of expert systems to organize and query image collections more efficiently. Recommendation systems that handle scientific images are rare, particularly if records lack metadata. This paper introduces new strategies to enable fast searches...

https://conf.slac.stanford.edu/ssrl-lcls

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provi...

High-throughput medical imaging procedures, such as echocardiogram, motivate the development of new computational tools to support specialists in decision making. This paper introduces a method to detect the posterior wall of the left ventricle from echocardiogram images, considering the PLAX view. Using a Light Gradient Boosting Machine, we evalua...

A new tool is introduced for screening macromolecular X-ray crystallography diffraction images produced at an X-ray free-electron laser light source. Based on a data-driven deep learning approach, the proposed tool executes a convolutional neural network to detect Bragg spots. Automatic image processing algorithms described can enable the classific...

Markov random fields (MRF) based algorithms have attracted a large amount of interest in image analysis due to their ability to exploit contextual information about data. Image data generated by experimental facilities, though, continues to grow larger and more complex, making it more difficult to analyze in a reasonable amount of time. Applying im...

Three-dimensional (3D) micro-tomography (µ-CT) has proven to be an important imaging modality in industry and scientific domains. Understanding the properties of material structure and behavior has produced many scientific advances. An important component of the 3D µ-CT pipeline is image partitioning (or image segmentation), a step that is used to...

There is an increasing interest in learning outside of the traditional classroom setting. This is especially true for topics covering computational tools and data science, as both are challenging to incorporate in the standard curriculum. These atypical learning environments offer new opportunities for teaching, particularly when it comes to combin...

Block copolymers serve as architecture-directing agents for the assembly of colloidal nanocrystals into a variety of mesoporous solids. Here we report the fundamental order-disorder transition in such assemblies, which yield, on one hand, ordered colloidal nanocrystals frameworks or, alternatively, disordered mesoporous nanocrystal films. Our deter...

There is an increasing interest in learning outside of the traditional classroom setting, especially for instruction of computational tools and practices that are challenging to incorporate in the standard curriculum. These atypical learning environments offer new ways for teaching students skills and concepts, particularly when it comes to combini...

Background: Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies...

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments effici...

This paper describes a variety of experiments that reveal the potential application of impedance spectroscopy (IS) measurements to enhance performance of ultrathin polyaniline (PANI)-based films on flexible substrate to control ammonia gas exposure in the 0–20 ppm range. Further, the device is mechanically robust for making electrical contact witho...

A sample of a nanomaterial contains a distribution of nanoparticles of various shapes and/or sizes. A scanning electron microscopy image of such a sample often captures only a fragment of the morphological variety present in the sample. In order to quantitatively analyse the sample using scanning electron microscope digital images, and, in particul...

Today users visit synchrotrons as sources of understanding and discovery—not as sources of just light, and not as sources of data. To achieve this, the synchrotron facilities frequently provide not just light but often the entire end station and increasingly, advanced computational facilities that can reduce terabytes of data into a form that can r...

Markov Random Field (MRF) algorithms are powerful tools in image analysis to explore contextual information of data. However, the application of these methods to large data means that alternative approaches must be found to circumvent the NP-hard complexity of the MRF optimization. We introduce a MRF-based framework that overcomes this issue by usi...

Synchrotrons such as the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory are user facilities - they are sources of extremely bright X-ray beams, and scientists come from all over the world to perform experiments that require these beams. As the complexity of experiments has increased, and the size and rates of data sets has exp...

In this paper we introduce and evaluate the systems submitted to the first Overlapping Cervical Cytology Image Segmentation Challenge, held in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2014. This challenge was organized to encourage the development and benchmarking of techniques capable of segmenting individual...

With the increasing access to pharmaceuticals, chances are that medication administration errors will occur more frequently. On average, individuals above age 65 take at least 14 prescriptions per year. Unfortunately, adverse drug reactions and noncompliance are responsible for 28 % of hospitalizations of the elderly. Correctly identifying pills ha...

Designing materials that are resistant to extreme temperatures and brittleness relies on assessing structural dynamics of samples. Algorithms are critically important to characterize material deformation under stress conditions. Here, we report on our design of coarse-grain parallel algorithms for image quality assessment based on structural inform...

Block copolymers are frequently used as architecture-directing agents during the construction of periodic mesoporous organosilicas (PMOs). Here, we describe new architecture-directing agents based on poly(N,N-dimethylacrylamide)-block-poly(styrene) block copolymers (BCPs) that allow PMOs to be generated in a simple spin-on fashion with independentl...

Cell occlusion, staining variation, particulate forms and diversity of cervical cells are some of the challenges in automating cervical cytology. This paper tackles some of these issues, including the detection of nucleus and cytoplasm from a new standardization for specimen preparation through mono/thin-layer technology. Our approach consists of t...