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<!DOCTYPE html>
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content="Bone Age Assessment Resources">
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<h1 class="title is-1 publication-title">Bone Age Assessment Resources</h1>
<br/>
<h2 class="subtitle has-text-justified">
Bone Age Assessment (BAA) is a critical factor for determining delayed development in children, which can be a sign of pathologies such as endocrine diseases,
growth abnormalities, chromosomal, neurological and congenital disorders among others. Typically, specialists such as pediatric endocrinologists inspect
visually an X-ray of the non-dominant hand of the child, and compare them against examples from textbook atlases to estimate Bone Age and predict adult height.
However, manual approaches are prone to intra and inter observer errors due to the level of expertise of the radiologist
or possible variations in the radiograph. Hence the need for an automated method for BAA.
</h2>
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</section>
<section class="section">
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<h2 class="title is-2"><span class="dnerf">Datasets</span> </h2>
<!-- Interpolating. -->
<h3 class="title is-4">Radiological Hand Pose Estimation (RHPE)</h3>
<div class="column content has-text-justified">
<p>
We collect the Radiological Hand Pose Estimation (RHPE) data from Colombian patients of the Fundación Santa Fe de Bogotá.
The database comprises images of radiographs taken from left and right hands of both male
and female patients between 0 and 240 months of age (0-20 years), with bone age annotations
made by two expert radiologists for each patient. The dataset is composed of 6,279 images
divided into 3 sets: 5,487 for training, 713 for validation and 79 for testing, maintaining
the proportion of images used in each split of the RSNA dataset. A similar bone age distribution
between the datasets suggests that they are compatible and can be used to study the influence of
ethnicity on bone age assessment algorithms.
</p>
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<span>Train</span>
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class="external-link button is-normal is-rounded is-dark">
<span>Validation</span>
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class="external-link button is-normal is-rounded is-dark">
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<img src="./static/images/overview_rhpe.png"
class="interpolation-image"
alt="Interpolate start reference image."/>
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<h3 class="title is-4">Radiological Society of North America (RSNA)</h3>
<div class="column content has-text-justified">
<p>
In 2017, the Radiological Society of North America (RSNA) created the Pediatric Bone Age Challenge.
The data was provided by Stanford University, the University of Colorado and the University of California - Los Angeles. The database comprises images
in png format of radiographs taken from the non-dominant hand of both male and female patients between 0
and 240 months of age (0-20 years), with bone age annotations made by trained radiologists. The dataset
is composed of 14,236 images divided into 3 sets: 12,611 for training, 1,425 for validation and 200 for
testing.
</p>
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<div class="publication-links">
<!-- PDF Link. -->
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class="external-link button is-normal is-rounded is-dark">
<span>Train</span>
</a>
</span>
<span class="link-block">
<a href="https://drive.google.com/file/d/17JM6Y5VeVgS35ywTKJ1U5CqHhDsF8irf/view"
class="external-link button is-normal is-rounded is-dark">
<span>Validation</span>
</a>
</span>
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<a href="https://drive.google.com/file/d/1-8akTtn8rAf4cQklIJQ1NUbFnTlGocgc/view"
class="external-link button is-normal is-rounded is-dark">
<span>Test</span>
</a>
</span>
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<a href="https://drive.google.com/file/d/1mOveYqmsiiONFxAUhDCWaFvCnq6GSIRl/view"
class="external-link button is-normal is-rounded is-dark">
<span>Annotations</span>
</a>
</span>
</div>
</div>
<div class="content has-text-centered">
<img src="./static/images/overview_rsna.png"
class="interpolation-image"
alt="Interpolate start reference image."/>
</div>
</div>
</div>
</div>
<div class="columns is-centered">
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<h2 class="title is-2">Publications</h2>
<div class="column has-text-centered">
<h2 class="title is-3 publication-title">SIMBA: Specific Identity Markers for Bone Age Assessments</h2>
<div class="is-size-5 publication-authors">
<span class="author-block">Cristina González<sup>*1</sup>,</span>
<span class="author-block">Maria Escobar<sup>*1</sup>,</span>
<span class="author-block">Laura Daza<sup>1</sup>,</span>
<span class="author-block">Felipe Torres<sup>1</sup>,</span>
<p></p>
<span class="author-block">Gustavo Triana<sup>2</sup>,</span>
<span class="author-block">Pablo Arbeláez<sup>1</sup>,</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>CINFONIA, Universidad de Los Andes, </span>
<span class="author-block"><sup>2</sup>Fundación Santa Fé de Bogotá </span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>*</sup>Denotes equal contribution.</span>
<p></p>
<span class="author-block">Poster at MICCAI 2020</span>
</div>
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<div class="publication-links">
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class="external-link button is-normal is-rounded is-dark">
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<a href="https://arxiv.org/abs/2007.05454"
class="external-link button is-normal is-rounded is-dark">
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</span>
<span>arXiv</span>
</a>
</span>
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<a href="https://github.com/BCV-Uniandes/SIMBA"
class="external-link button is-normal is-rounded is-dark">
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<span>Code</span>
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<div class="content has-text-justified">
<p>
Bone Age Assessment (BAA) is a task performed by radiologists to diagnose abnormal growth in a child.
In manual approaches, radiologists take into account different dentity markers when calculating bone age, i.e.,
chronological age and gender. However, the current automated Bone Age Assessment methods do not completely exploit
the information present in the patient's metadata. With this lack of available methods as motivation, we present
SIMBA: Specific Identity Markers for Bone Age Assessment. SIMBA is a novel approach for the task of BAA based on
the use of identity markers.
</p>
<p>
For this purpose, we build upon the state-of-the-art model, fusing the information present in the identity markers
with the visual features created from the original hand radiograph. We then use this robust representation to
estimate the patient's relative bone age: the difference between chronological age and bone age. We validate
SIMBA on the Radiological Hand Pose Estimation dataset and find that it outperforms previous state-of-the-art
methods. SIMBA sets a trend of a new wave of Computer-aided Diagnosis methods that incorporate all of the data
that is available regarding a patient. To promote further research in this area and ensure reproducibility we
will provide the source code as well as the pre-trained models of SIMBA.
</p>
</div>
</div>
<br/>
<div class="column has-text-centered">
<h2 class="title is-3 publication-title">Hand Pose Estimation for Pediatric Bone Age Assessment</h2>
<div class="is-size-5 publication-authors">
<span class="author-block">Maria Escobar<sup>*1</sup>,</span>
<span class="author-block">Cristina González<sup>*1</sup>,</span>
<span class="author-block">Felipe Torres<sup>1</sup>,</span>
<span class="author-block">Laura Daza<sup>1</sup>,</span>
<p></p>
<span class="author-block">Gustavo Triana<sup>2</sup>,</span>
<span class="author-block">Pablo Arbeláez<sup>1</sup>,</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>CINFONIA, Universidad de Los Andes, </span>
<span class="author-block"><sup>2</sup>Fundación Santa Fé de Bogotá </span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>*</sup>Denotes equal contribution.</span>
<p></p>
<span class="author-block">Oral presentation at MICCAI 2019</span>
</div>
<div class="column has-text-centered">
<div class="publication-links">
<!-- PDF Link. -->
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<a href="https://link.springer.com/chapter/10.1007/978-3-030-32226-7_59"
class="external-link button is-normal is-rounded is-dark">
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<span>Paper</span>
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<a href="https://cinfonia.uniandes.edu.co/wp-content/uploads/2021/06/Hand_Pose_Estimation_for_Pediatric_Bone_Age_Assessment.pdf"
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<span>arXiv</span>
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<p>
We present a new experimental framework for the task of Bone Age Assessment (BAA) based on a local
analysis of anatomical Regions Of Interest (ROIs) of hand radiographs. For this purpose, we introduce the
Radiological Hand Pose Estimation (RHPE) Dataset, composed of 6,288 hand radiographs from a
population that is different from the currently available BAA datasets. We provide Bone Age groundtruths
annotated by two expert radiologists as well as bounding boxes and keypoints denoting anatomical ROIs
annotated by multiple trained subjects. In addition to RHPE, we provide bounding boxes and ROIs
annotations for the publicly available BAA dataset by the Radiological Society of North America (RSNA). We propose a new experimental framework with hand detection and hand pose estimation as new tasks
to extract local information for BAA methods. Thanks to its fine-grained and precisely localized
annotations, our dataset will allow to exploit local information to push forward automated BAA
algorithms. Additionally, we conduct experiments with state-of-the-art methods in each of the new tasks.
Our proposed model, named BoNet, leverages local information and significantly outperforms state-of-the-
art methods in BAA. We provide the RHPE dataset with the corresponding annotations, as well as the
trained models, the source code for BoNet and the additional annotations created for the RSNA dataset.
</p>
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<h2 class="title">BibTeX</h2>
<pre><code>
@inproceedings{escobar2019hand,
title={Hand Pose Estimation for Pediatric Bone Age Assessment},
author={Escobar, Mar{\'\i}a and Gonz{\'a}lez, Cristina and Torres, Felipe and Daza, Laura and Triana, Gustavo and Arbel{\'a}ez, Pablo},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={531--539},
year={2019},
organization={Springer}
}
</code></pre>
<pre><code>
@inproceedings{gonzalez2020simba,
title={SIMBA: Specific Identity Markers for Bone Age Assessment},
author={Gonz{\'a}lez, Cristina and Escobar, Mar{\'\i}a and Daza, Laura and Torres, Felipe and Triana, Gustavo and Arbel{\'a}ez, Pablo},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={753--763},
year={2020},
organization={Springer}
}
</code></pre>
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