Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans

Kuang, Hulin; Wang, Yahui; Liu, Jin; Wang, Jie; Cao, Quanliang; Hu, Bo; Qiu, Wu; Wang, Jianxin

doi:10.1109/tmi.2024.3362879

Cited by 6 publications

(2 citation statements)

References 49 publications

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“…In clinical practice, the volume correlation as well as the infarct volume (e.g., 70 mL as the cut-off) are crucial for selecting AIS patients who will obtain good outcomes after different treatments [ 31 , 44 , 45 ]. Therefore, we also conducted a volume analysis on the ischemic infarcts obtained by our method to illustrate the clinical relevance of the proposed method.…”

Section: Resultsmentioning

confidence: 99%

Segmenting Ischemic Penumbra and Infarct Core Simultaneously on Non-Contrast CT of Patients with Acute Ischemic Stroke Using Novel Convolutional Neural Network

Kuang,

Tan,

Wang

et al. 2024

Biomedicines

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Differentiating between a salvageable Ischemic Penumbra (IP) and an irreversibly damaged Infarct Core (IC) is important for therapy decision making for acute ischemic stroke (AIS) patients. Existing methods rely on Computed Tomography Perfusion (CTP) or Diffusion-Weighted Imaging–Fluid Attenuated Inversion Recovery (DWI-FLAIR). We designed a novel Convolutional Neural Network named I2PC-Net, which relies solely on Non-Contrast Computed Tomography (NCCT) for the automatic and simultaneous segmentation of the IP and IC. In the encoder, Multi-Scale Convolution (MSC) blocks were proposed to capture effective features of ischemic lesions, and in the deep levels of the encoder, Symmetry Enhancement (SE) blocks were also designed to enhance anatomical symmetries. In the attention-based decoder, hierarchical deep supervision was introduced to address the challenge of differentiating between the IP and IC. We collected 197 NCCT scans from AIS patients to evaluate the proposed method. On the test set, I2PC-Net achieved Dice Similarity Scores of 42.76 ± 21.84%, 33.54 ± 24.13% and 65.67 ± 12.30% and lesion volume correlation coefficients of 0.95 (p < 0.001), 0.61 (p < 0.001) and 0.93 (p < 0.001) for the IP, IC and IP + IC, respectively. The results indicated that NCCT could potentially be used as a surrogate technique of CTP for the quantitative evaluation of the IP and IC.

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Section: Resultsmentioning

confidence: 99%

Segmenting Ischemic Penumbra and Infarct Core Simultaneously on Non-Contrast CT of Patients with Acute Ischemic Stroke Using Novel Convolutional Neural Network

Kuang,

Tan,

Wang

et al. 2024

Biomedicines

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“…Therapeutic Applications and Treatment Planning: AI is shown to support therapeutic planning and intervention strategies. One study, for instance, explores how AI can guide the administration of treatments in real time by accurately scoring collateral circulation in stroke patients using hybrid CNN and transformer networks [ 4 ].…”

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confidence: 99%