Table 2.

Performance comparison of MDL algorithm and graph morphology method without MDL

All datasets		Number of spines	Number of other protrusions	MDL algorithm			Graph morphology without MDL
				False negative	False negative rate	False positive rate	False negative rate	False positive rate
Tracht6	A	41	45	3	7.3%	6.7%	17.1%	20.0%
	B	51	46	3	5.9%	4.3%	3.9%	78.3%
	C	50	47	2	4.0%	12.7%	14%	44.7%
	D	46	49	2	4.3%	14.3%	4.3%	46.9%
	E	39	44	4	10.3%	2.3%	15.4%	27.3%
	Overall	227	231	14	6.2%	8.1%	10.9%	43.4%
Tracht7	A	25	38	1	4.0%	3.2%	4.0%	29.0%
	B	25	39	1	4.0%	10.6%	76.0%	3.1%
	C	21	31	1	4.8%	6.0%	28.6%	68.0%
	D	24	29	2	8.3%	5.1%	20.8%	28.6%
	E	19	26	2	10.5	11.6%	63.2%	3.8%
	Overall	114	163	7	6.1%	6.5%	38.5%	26.5%
Tracht8	A	29	41	2	6.9%	18.8%	10.3%	48.6%
	B	28	39	2	7.1%	12.8%	7.1%	38.5%
	C	32	46	1	3.1%	17.1%	6.3%	40.0%
	D	32	47	2	6.3%	14.9%	6.3%	34.0%
	E	31	47	2	6.5%	14.9%	6.5%	42.6%
	Overall	152	220	9	5.9%	15.7%	7.3%	40.7%
Tracht11	A	43	49	3	7.0%	18.4%	9.3%	36.8%
	B	41	48	4	9.8%	18.8%	78.0%	2.1%
	C	45	50	3	6.7%	12.0%	8.9%	32.0%
	D	38	46	3	7.9%	13.0%	7.9%	32.6%
	Overall	167	193	13	7.8%	15.6%	20.0%	25.9%
Tracht14	A	27	31	1	3.7%	16.1%	3.7%	74.2%
	B	26	30	1	3.8%	3.3%	3.8%	26.7%
	C	29	33	2	6.9%	18.2%	6.9%	33.3%
	D	27	31	2	7.4%	0.0%	18.5%	6.5%
	E	32	36	3	8.3%	13.9%	40.6%	5.6%
	Overall	141	161	9	6.4%	10.3%	14.7%	29.3%
CalTech20m		81	98	9	11.1%	18.3%	21.0%	26.5%
CalTech100m		89	99	10	11.2%	20.2%	21.3%	35.4%
Pottert330		116	130	8	6.9%	12.3%	21.6%	20.8%
MBFsp5		227	230	17	7.5%	12.2%	17.6%	14.8%
MBFsp6		149	160	13	8.7%	15.0%	10.1%	23.1%
MBFsp8		82	90	11	13.4%	10.1%	26.8%	32.2%
Overall					7.1%	11.8%	18.8%	31.2%