Round Randomized Learning Vector Quantization for Brain Tumor Imaging

Table 1

UKM Medical Center axial sequence of brain tumor images: data set 1 (a) general and (b) specific.

(a)

Dataset name	Number of instances	Spatial resolution	Number of features	Number of classes	Source
Brain tumor images	505	768 × 768	21	2 (Normal, abnormal)	UKMMC
Class type		T1 Sub total		T2 Subtotal
Normal		158		75
Abnormal		187		85

(b)

Abnormal subclass type	Cancerous type	Number of patient data	Range of tumor size based on medical expert report
Abnormal (Grade 1)	CP meningioma	1	1.5 cm (AP) × 2 cm (W) × 1.9 cm (CC)
	Suprasellar mass	1	5.8 cm (AP) × 7.2 cm (W) × 6.2 cm (CC)
	Schwannoma with mild hydrocephalus	1	2.7 cm (AP) × 4.1 cm (W) × 4.8 cm (CC)
Abnormal (Grade 2)	Astrocytoma	1	4.4 cm (AP) × 2.7 cm (W) × 4.8 cm (CC)
	Hemangiopericytoma	1	1.2 cm (AP) × 1.3 cm (W) × 1 cm (CC)
	Atypical meningioma	1	2.6 cm (AP) × 1.8 cm (W) × 2.8 cm (CC)