RESUMO
Surgeons must visually distinguish soft-tissues, such as nerves, from surrounding anatomy to prevent complications and optimize patient outcomes. An accurate nerve segmentation and analysis tool could provide useful insight for surgical decision-making. Here, we present an end-to-end, automatic deep learning computer vision algorithm to segment and measure nerves. Unlike traditional medical imaging, our unconstrained setup with accessible handheld digital cameras, along with the unstructured open surgery scene, makes this task uniquely challenging. We investigate one common procedure, thyroidectomy, during which surgeons must avoid damaging the recurrent laryngeal nerve (RLN), which is responsible for human speech. We evaluate our segmentation algorithm on a diverse dataset across varied and challenging settings of operating room image capture, and show strong segmentation performance in the optimal image capture condition. This work lays the foundation for future research in real-time tissue discrimination and integration of accessible, intelligent tools into open surgery to provide actionable insights.
Assuntos
Aprendizado Profundo , Nervo Laríngeo Recorrente/cirurgia , Doenças da Glândula Tireoide/cirurgia , Tireoidectomia/métodos , Humanos , Nervo Laríngeo Recorrente/patologia , Doenças da Glândula Tireoide/patologia , Glândula Tireoide/patologia , Glândula Tireoide/cirurgiaRESUMO
"Normal values" for blood parameters of neonates are generally unavailable, because blood is not usually drawn on healthy, normal neonates to establish normal ranges. Instead, "reference ranges" are used, consisting of the 5th to the 95th percentile values compiled from tests performed on neonatal patients with minimal pathology, under the premise that such ranges approximate normal values. In recent years, we have been seeking to establish reference ranges for various elements of the complete blood count (CBC) of neonates, using the large databases of Intermountain Healthcare, a health care system in the western United States. Establishing these reference ranges has been facilitated by using modern hematology analyzers and electronic data repositories of clinical and laboratory information. The present review brings together several of our recent reports, displaying reference ranges for elements of the CBC among neonates at various gestational and postnatal ages.