Classification of Computed Tomography Images in Different Slice Positions Using Deep Learning

Table 1

Names of datasets and the number of images in each label.

	Names of datasets
	0.1K	0.5K	1K	2K	3K	4K	5K	6K	7K	8K	9K	10K	Testing dataset
Brain (P)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Brain (CE)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Neck (P)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Neck (CE)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Chest (P)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Chest (CE)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Abdomen (P)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Abdomen (CE)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Pelvis (P)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Pelvis (CE)	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	100
Total number of images	1000	5000	10,000	20,000	30,000	40,000	50,000	60,000	70,000	80,000	90,000	100,000	1000
For training	900	4500	9000	18,000	27,000	36,000	45,000	54,000	63,000	72,000	81,000	90,000	-
For validation	100	500	1000	2000	3000	4000	5000	6000	7000	8000	9000	10,000	-