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20182024
most citedBrain Tumor Image Retrieval via Multitask Learning

7 citations · 9 across the 10 of their papers we have counts for

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6 papers · 1 filter

eess.IV2024★ 1 cited

The impact of deep learning aid on the workload and interpretation accuracy of radiologists on chest computed tomography: a cross-over reader study

Anvar Kurmukov, Valeria Chernina, Regina Gareeva +18

Interpretation of chest computed tomography (CT) is time-consuming. Previous studies have measured the time-saving effect of using a deep-learning-based aid (DLA) for CT interpreta…

eess.IV2024

Hierarchical Loss And Geometric Mask Refinement For Multilabel Ribs Segmentation

Aleksei Leonov, Aleksei Zakharov, Sergey Koshelev +3

Automatic ribs segmentation and numeration can increase computed tomography assessment speed and reduce radiologists mistakes. We introduce a model for multilabel ribs segmentation…

eess.IV2022

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…

eess.IV2020

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…

eess.IV2020

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…

eess.IV2019★ 1 cited

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…