1 citations · 1 across the 5 of their papers we have counts for
5 papers
Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localization
Alexey Zakharov, Maxim Pisov, Alim Bukharaev +4
Vertebral body compression fractures are early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by radiologi…
CT-based COVID-19 Triage: Deep Multitask Learning Improves Joint Identification and Severity Quantification
Mikhail Goncharov, Maxim Pisov, Alexey Shevtsov +8
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody…
Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification
Maxim Pisov, Vladimir Kondratenko, Alexey Zakharov +4
Vertebral body compression fractures are reliable early signs of osteoporosis. Though these fractures are visible on Computed Tomography (CT) images, they are frequently missed by…
Discovery of Two Types of Twinkling Can Explain Contradictory Observations among Twinkling Artifact Investigators in Ultrasound Imaging
Denis Leonov, Nicholas Kulberg, Alexandr Gromov +2
Twinkling Artifact is a valuable tool in detecting dense objects such as kidney stones, calculi etc., especially when there is no acoustic shadowing and presence of hyperechogenic…
Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection
Maxim Pisov, Mikhail Goncharov, Nadezhda Kurochkina +9
Midline shift (MLS) is a well-established factor used for outcome prediction in traumatic brain injury, stroke and brain tumors. The importance of automatic estimation of MLS was r…