Machine learning that can identify and localize objects in an image using a labeled bounding box is called object detection. The purpose of this study is to demonstrate object detection in identifying rickets on pediatric wrist radiographs. Read More

Meeting name: SPR 2020 Annual Meeting & Postgraduate Course , 2020

Authors: Meda Karthik, Milla Sarah, Rostad Bradley

Keywords: Machine learning, Artificial intelligence, rickets

Ulcerative colitis (UC) and Crohn disease are chronic, immune-mediated, inflammatory disorders of the gastrointestinal tract collectively referred to as inflammatory bowel disease (IBD). As many of 20-25% of patients with IBD initially present in childhood or adolescence, and the incidence of pediatric IBD is increasing. IBD primarily affects the bowel, but other organs can be involved. Nearly one-third of patients will have at least one extra-intestinal manifestation. Some extra-intestinal manifestations, such as that between UC and primary sclerosing cholangitis (PSC), are well-established. Others are less understood and may mimic more common pathology, particularly infection. Therefore, pediatric radiologists must become familiar with these extra-intestinal manifestations and consider the diagnosis of IBD as the etiology for their pathology. Read More

Meeting name: SPR 2018 Annual Meeting & Postgraduate Course , 2018

Authors: Joshi Hena, Alazraki Adina, Rostad Bradley

Keywords: inflammatory bowel disease, ulcerative colitis, Crohn disease

Foreign body ingestion is common in children. Timely diagnosis of the nature and location of the foreign body is important. A button battery which lodges in the esophagus can quickly cause severe esophageal and mediastinal injury. Machine learning that can detect anatomical regions of interest is an important step in computerized foreign body localization and may result in prioritization of radiographs with mediastinal foreign bodies. The purpose of this study is to develop a machine learning model to identify anatomical regions of interest on pediatric foreign body series radiographs. Read More

Meeting name: SPR 2020 Annual Meeting & Postgraduate Course , 2020

Authors: Rostad Bradley, Richer Edward, Riedesel Erica, Alazraki Adina

Keywords: Machine learning, Artificial intelligence, Foreign body

Timely diagnosis of foreign body ingestion in children is important, particularly in the case of an ingested button battery. A button battery which lodges in the esophagus can quickly cause severe esophageal and mediastinal injury. It is also important to distinguish an ingested button battery from a coin; a button battery may be misdiagnosed a coin because of its similar radiographic appearance. The purpose of this study is to develop a machine learning model to identify button batteries and coins on pediatric foreign body series radiographs. Read More

Meeting name: SPR 2020 Annual Meeting & Postgraduate Course , 2020

Authors: Rostad Bradley, Richer Edward, Riedesel Erica, Alazraki Adina

Keywords: Machine learning, Artificial intelligence, Button battery