Computer-Aided Evaluation of Ki-67 on Pathological Sections of Appendiceal Neuroendocrine Neoplasms

zhenzhen Wan; Shaoyong Zhang; Fang Liu; Ning Shi; Shuai Han; Chunxue Li

doi:10.3788/LOP202158.2417001

Laser & Optoelectronics Progress, Volume. 58, Issue 24, 2417001(2021)

Computer-Aided Evaluation of Ki-67 on Pathological Sections of Appendiceal Neuroendocrine Neoplasms

zhenzhen Wan¹, Shaoyong Zhang¹, Fang Liu^3,4, Ning Shi^2、*, Shuai Han¹, and Chunxue Li¹

Author Affiliations

¹College of Electronic Information Engineering, Hebei University, Baoding, Hebei 0 71002, China

²Hebei Software Institute, Baoding, Hebei 0 71030, China

³Pathology Department, Baoding Children's Hospital, Baoding, Hebei 0 71051, China

⁴Key Laboratory of Clinical Research on Children's Respiratory Digestive Diseases in Baoding City, Baoding, Hebei 0 71051, China

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Figures & Tables(15)

Fig. 1. Pathological section of ANENs

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Fig. 2. Overall design flow chart of the system scheme

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Fig. 3. Image of ANENs pathological section (left) and color image of YUV (right)

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Fig. 4. YUV spatial threshold segmentation images. (a) Threshold segmentation image of positive cell; (b) threshold segmentation image of negative cells

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Fig. 5. Images processed by mathematical morphology. (a) Positive cell; (b) negative cells

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Fig. 6. One-dimensional minimum highlight process. (a) One-dimensional data; (b) minimum highlight results

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Fig. 7. Positive cells processing images obtained by improved watershed algorithm. (a) Image of ANENs pathological section; (b) distance transform image; (c) image by forced minimum technique processing; (d) image processed by improved watershed algorithm; (e) binary segmentation image; (f) color marker segmentation image

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Fig. 8. Negative cells processing images obtained by improved watershed algorithm. (a) Image of ANENs pathological section; (b) distance transform images; (c) image by forced minimum technique processing; (d) image processed by improved watershed algorithm; (e) binary segmentation image; (f) color marker segmentation image

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Fig. 9. Negative cells segmentation effect diagrams before and after algorithm improvement. (a)--(c) Traditional watershed algorithm; (d)--(f) improved watershed algorithm

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Fig. 10. Over-segmentation rate data of negative cells

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Fig. 11. Data analysis of Ki-67 index

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Fig. 12. Comparison of time consumption on image processing

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Table 1. Experimental data of positive cells in ANENs pathological section images obtained by improved watershed algorithm
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Table 1. Experimental data of positive cells in ANENs pathological section images obtained by improved watershed algorithm
Cell image No. Quantity of positive cells Diagnostic requirement
Doctor Traditional algorithm Improved algorithm
1 10 12 10 Yes
2 11 13 11 Yes
3 12 14 12 Yes
4 9 12 9 Yes
5 8 11 8 Yes
6 13 15 12 Yes
7 11 13 11 Yes
8 10 12 10 Yes

Table 2. Experimental data of negative cells in ANENs pathological section images

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Table 2. Experimental data of negative cells in ANENs pathological section images

No.	Negative cell number from doctor	Negative cell number from traditional algorithm	Over-segmentation rate from traditional algorithm /%	Negative cell number from improved algorithm	Over-segmentation rate from improved algorithm /%	Improved algorithm’s accuracy /%
1	423	524	10.7	454	3.5	92.7
2	430	531	10.5	465	3.9	91.9
3	428	516	9.3	468	4.5	90.7
4	370	452	10.0	391	2.8	94.3
5	351	443	11.7	368	2.4	95.2
6	480	576	9.1	496	1.6	96.7
7	421	524	10.9	457	4.1	91.4
8	408	498	9.9	430	2.6	94.6

Table 3. Experimental data of diagnostic indicators of ANENs pathological sections

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Table 3. Experimental data of diagnostic indicators of ANENs pathological sections

Experimental group No.	Ki-67 index from doctor /%	Ki-67 index from computer /%	Ki-67 accuracy rate by computer /%	Doctor’s time consumption /s	Computer’s time consumption /s	Error rate from computer /%	Diagnostic value	Diagnostic requirements
1	2.31	2.16	93.5	58	29	6.5	<3%	Yes
2	2.50	2.31	92.4	59	28	7.6	<3%	Yes
3	2.73	2.50	91.6	60	30	8.4	<3%	Yes
4	2.37	2.25	95.0	55	32	5.0	<3%	Yes
5	2.23	2.12	95.0	54	31	5.0	<3%	Yes
6	2.60	2.36	90.8	58	33	9.2	<3%	Yes
7	2.55	2.35	92.2	62	27	7.8	<3%	Yes
8	2.39	2.27	94.9	53	26	5.1	<3%	Yes

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zhenzhen Wan, Shaoyong Zhang, Fang Liu, Ning Shi, Shuai Han, Chunxue Li. Computer-Aided Evaluation of Ki-67 on Pathological Sections of Appendiceal Neuroendocrine Neoplasms[J]. Laser & Optoelectronics Progress, 2021, 58(24): 2417001

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Paper Information

Category: Medical Optics and Biotechnology

Received: Jan. 8, 2021

Accepted: Mar. 12, 2021

Published Online: Dec. 1, 2021

The Author Email: Ning Shi (emailshining@126.com)

DOI:10.3788/LOP202158.2417001

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Experimental data of positive cells in ANENs pathological section images obtained by improved watershed algorithm

Table 1. Experimental data of positive cells in ANENs pathological section images obtained by improved watershed algorithm

Table 2. Experimental data of negative cells in ANENs pathological section images

Table 2. Experimental data of negative cells in ANENs pathological section images

Table 3. Experimental data of diagnostic indicators of ANENs pathological sections

Table 3. Experimental data of diagnostic indicators of ANENs pathological sections