---
license: mit
tags:
  - deep-learning
  - computer-vision
  - image-classification
  - transfer-learning
  - biomedical-imaging
  - pytorch
task:
  - image-classification
language: en
datasets:
  - ImageNet
  - RadImagenet
library_name: PyTorch
---

# Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting Operation

This repository introduces **Cross-D Conv**, a novel convolutional operation designed to bridge the dimensional gap between 2D and 3D medical imaging datasets. By leveraging the Fourier domain for phase shifting, Cross-D Conv enables seamless weight transfer between 2D and 3D convolutional operations. This method addresses the challenge of multimodal data scarcity by utilizing abundant 2D data to enhance 3D model performance effectively.

```bibtex
@article{yavuz2024cross,
  title={Cross-D Conv: Cross-Dimensional Transferable Knowledge Base via Fourier Shifting Operation},
  author={Yavuz, Mehmet Can and Yang, Yang},
  journal={arXiv preprint arXiv:2411.02441},
  year={2024}
}
```

## Performance Metrics

### Table 1: ResNet18 Performance on Imagenet and RadImagenet
| Dataset | Model          | Precision (Macro) | Recall (Macro) | F1 (Macro) | Balanced Accuracy | Average Accuracy |
|---------|----------------|-------------------|----------------|------------|-------------------|------------------|
| IN1K    | Regular        | 0.6807           | 0.6693         | 0.6657     | 0.6693           | 0.6693          |
|         | **Cross-D Conv** | **0.6895**       | **0.6881**     | **0.6838** | **0.6881**       | **0.6881** ↑    |
| RIN     | Regular        | 0.5830           | 0.4989         | 0.5252     | 0.4989           | 0.8305          |
|         | **Cross-D Conv** | **0.5891**       | **0.5228**     | **0.5471** | **0.5228**       | **0.8374** ↑    |

### Table 2: Performance on Image Datasets
| Dataset | Method        | OrganC Mean ± Std (CT) | OrganS Mean ± Std (CT) | Brain Tumor Mean ± Std (MRI) | Brain Dataset Mean ± Std (MRI) | Breast Mean ± Std (US) | Breast Cancer Mean ± Std (US) | Average |
|---------|---------------|------------------------|-------------------------|------------------------------|---------------------------------|------------------------|-------------------------------|---------|
| IN1K    | 2D Conv       | 0.862 ± 0.006         | 0.708 ± 0.035          | 0.884 ± 0.011               | 0.305 ± 0.023                 | 0.819 ± 0.019          | 0.745 ± 0.024                | 0.720   |
|         | **Cross-D Conv** | **0.871 ± 0.007**   | **0.763 ± 0.008**      | **0.892 ± 0.010**           | **0.308 ± 0.026**             | **0.836 ± 0.021**      | **0.759 ± 0.022**            | **0.738** ↑ |
| RIN     | 2D Conv       | 0.842 ± 0.006         | 0.742 ± 0.008          | 0.902 ± 0.010               | 0.268 ± 0.023                 | 0.832 ± 0.021          | 0.762 ± 0.016                | 0.725   |
|         | **Cross-D Conv** | **0.848 ± 0.008**   | **0.743 ± 0.008**      | **0.910 ± 0.013**           | **0.283 ± 0.023**             | **0.835 ± 0.037**      | **0.747 ± 0.024**            | **0.728** |

### Table 3: Performance on Volumetric Datasets
| Dataset | Method        | Mosmed Mean ± Std (CT) | Lung Aden. Mean ± Std (CT) | Fracture Mean ± Std (CT) | BraTS21 Mean ± Std (MRI) | IXI Mean ± Std (MRI) | BUSV Mean ± Std (US) | Average |
|---------|---------------|------------------------|----------------------------|--------------------------|--------------------------|-----------------------|-----------------------|---------|
| IN1K    | ACS-Conv      | **0.523 ± 0.057**     | **0.532 ± 0.034**         | 0.456 ± 0.027           | 0.539 ± 0.030           | 0.542 ± 0.044        | 0.559 ± 0.079        | 0.525   |
|         | **Cross-D Conv** | 0.505 ± 0.068      | 0.513 ± 0.071             | **0.469 ± 0.027**       | **0.549 ± 0.031**       | **0.583 ± 0.059**    | **0.590 ± 0.064**    | **0.535** ↑ |
| RIN     | ACS-Conv      | 0.547 ± 0.072         | **0.548 ± 0.034**         | 0.471 ± 0.034           | 0.545 ± 0.041           | 0.555 ± 0.046        | **0.604 ± 0.063**    | 0.545   |
|         | **Cross-D Conv** | **0.557 ± 0.102**   | 0.529 ± 0.058             | **0.491 ± 0.032**       | **0.558 ± 0.044**       | **0.559 ± 0.050**    | 0.602 ± 0.066        | **0.549** |

---
license: mit
---