Pulmonary Embolism Detection

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (11 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
  15 Sep 2021 2 repositories listed
  At the image level, we compare convolutional neural networks (CNNs) with vision transformers, and contrast self-supervised learning (SSL) with supervised learning, followed by an evaluation of transfer learning compared…
• Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
  19 Aug 2019 2 repositories listed
  More importantly, learning a model from scratch simply in 3D may not necessarily yield performance better than transfer learning from ImageNet in 2D, but our Models Genesis consistently top any 2D approaches including…
• PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis
  27 Aug 2023 1 repository listed
  Previous deep learning efforts have focused on improving the performance of Pulmonary Embolism(PE) diagnosis from Computed Tomography (CT) scans using Convolutional Neural Networks (CNN).
• Estimating Total Lung Volume from Pixel-level Thickness Maps of Chest Radiographs Using Deep Learning
  24 Oct 2021 1 repository listed
  Synthetic radiographs and lung thickness maps were generated using forward projection of CT scans and their lung segmentations.