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New LaryngealCT Dataset Benchmarks Deep Learning for Cancer Staging

By PulseAugur Editorial · [1 sources] ·

Researchers have developed LaryngealCT, a new benchmark dataset for staging laryngeal cancer using deep learning models. The dataset comprises 1,029 CT scans aggregated from The Cancer Imaging Archive and has been used to benchmark six different 3D deep learning architectures. The custom 3D CNN achieved the highest performance in classifying early versus advanced stages of the cancer, while other models showed promise in identifying T4 stage disease, though sensitivity for this advanced stage remains a challenge. AI

IMPACT Establishes a reproducible benchmark for AI-driven laryngeal cancer staging, potentially accelerating clinical decision-making.

RANK_REASON The cluster contains an academic paper detailing a new dataset and benchmarking of deep learning models for a specific medical application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LaryngealCT Dataset Benchmarks Deep Learning for Cancer Staging

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The cluster contains an academic paper detailing a new dataset and benchmarking of deep learning models for a specific medical application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Nivea Roy, Son Tran, Atul Sajjanhar, K. Devaraja, Prakashini Koteshwara, Yong Xiang, Divya Rao ·

    Benchmarking Deep Learning Models for Laryngeal Cancer Staging Using the LaryngealCT Dataset

    arXiv:2510.11047v2 Announce Type: replace Abstract: Laryngeal cancer imaging research lacks standardised public datasets to enable reproducible deep learning (DL) model development. We present LaryngealCT, a curated benchmark of 1,029 computed tomography (CT) scans aggregated fro…

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