Multi-Scale Context-Guided Lumbar Spine Disease Identification with Coarse-to-fine Localization and Classification

Introduction

This repository is the official PyTorch implementation of CCF-Net (Multi-Scale Context-Guided Lumbar Spine Disease Identification with Coarse-to-fine Localization and Classification), ISBI 2022 (Oral). CCF-Net is also the runner-up solution of the 2020 Spinal Disease Intelligent Diagnosis AI Challenge. The link to the paper is here.

Requirements

Pytorch>=1.1.0
CPU or GPU
Other packages can be installed with the following command:

pip install requirements.txt

Quick start

Dataset is provided in TianChi platform.

Once the data is ready, you can run the code with the following command.

python main_ours_resnet50_msc.py

Results

Method	Backbone	Params (M)	Flops (G)	L-Disc	L-Vertebra	C-Disc	C-Vertebra	Score
SimpleBaseline	ResNet18	15.38	33.23	87.81	86.11	89.26	71.71	70.70
SimpleBaseline	ResNet18-MSC	6.86	33.50	91.80	92.94	88.20	74.47	75.13
SCN	ResNet18	26.57	42.73	88.56	88.77	89.26	71.18	71.18
SCN	ResNet18-MSC	11.62	45.43	92.79	94.13	90.16	75.94	77.64
CCF-Net (ours)	ResNet18	9.51	11.20	89.69	89.23	89.32	76.23	74.05
CCF-Net (ours)	ResNet18-MSC	4.83	12.00	94.75	94.71	90.88	79.16	80.50

Method	Backbone	Params (M)	Flops (G)	L-Disc	L-Vertebra	C-Disc	C-Vertebra	Score
SimpleBaseline	ResNet50	34.00	51.64	89.33	90.07	90.21	76.06	74.59
SimpleBaseline	ResNet50-MSC	45.33	124.80	94.53	94.54	90.56	76.06	78.77
HRNet	W32	28.54	40.98	96.19	95.63	89.68	78.43	80.62
CCF-Net (ours)	ResNet50	23.60	21.49	90.43	90.24	90.06	76.35	75.13
CCF-Net (ours)	ResNet50-MSC	10.79	22.09	85.68	96.41	90.59	77.46	80.64

Citation