PHE-SICH-CT-IDS: A Benchmark CT Image Dataset for Evaluation Semantic Segmentation, Object Detection and Radiomic Feature Extraction of Perihematomal Edema in Spontaneous Intracerebral Hemorrhage
Deguo Ma, Chen Li, Lin Qiao, Tianming Du, Dechao Tang, Zhiyu Ma,, Marcin Grzegorzek Hongzan, Hongzan Sun

TL;DR
This paper introduces PHE-SICH-CT-IDS, a comprehensive public CT image dataset for perihematomal edema in spontaneous intracerebral hemorrhage, facilitating advancements in segmentation, detection, and radiomic analysis methods.
Contribution
It provides the first publicly available, multi-format CT dataset for PHE in SICH, supporting research and development of diagnostic algorithms.
Findings
Classical algorithms effectively evaluate dataset suitability
Dataset covers diverse medical data formats
Supports development of novel diagnostic methods
Abstract
Intracerebral hemorrhage is one of the diseases with the highest mortality and poorest prognosis worldwide. Spontaneous intracerebral hemorrhage (SICH) typically presents acutely, prompt and expedited radiological examination is crucial for diagnosis, localization, and quantification of the hemorrhage. Early detection and accurate segmentation of perihematomal edema (PHE) play a critical role in guiding appropriate clinical intervention and enhancing patient prognosis. However, the progress and assessment of computer-aided diagnostic methods for PHE segmentation and detection face challenges due to the scarcity of publicly accessible brain CT image datasets. This study establishes a publicly available CT dataset named PHE-SICH-CT-IDS for perihematomal edema in spontaneous intracerebral hemorrhage. The dataset comprises 120 brain CT scans and 7,022 CT images, along with corresponding…
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Taxonomy
TopicsIntracerebral and Subarachnoid Hemorrhage Research · Acute Ischemic Stroke Management
