{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:22:25Z","timestamp":1760059345294,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T00:00:00Z","timestamp":1749427200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research Project of Liaoning Province Science and Technology Plan Joint Program","award":["2024JH2\/102600063"],"award-info":[{"award-number":["2024JH2\/102600063"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Classifying newly formed colonies is instrumental in uncovering sources of infection and enabling precision medicine, holding significant clinical value. However, due to the ambiguous features of early-stage colony images in culture dishes, conventional computer vision (CV) classification algorithms are often ineffective. To achieve accurate and efficient colony classification, this paper proposes a high-precision method based on Persistent Homology (PH) and an improved EfficientNet. Specifically, (1) a PH feature extraction algorithm is applied to Candida albicans (CA) and Staphylococcus epidermidis (SE) colonies cultured for 18 h in Petri dishes to capture their topological information. (2) The Mobile Inverted Bottleneck Convolution (MBConv) module in EfficientNet is modified, enhancing the attention mechanism to better handle local small targets. (3) A novel self-attention mechanism named the Spatial and Contextual Transformer (SCoT), which is introduced to process information at multiple scales, increasing the resolution in orthogonal directions of the image and the aggregation capability of feature maps. The proposed approach achieves a high accuracy of 98.64%, a 10.29% improvement over the original classification model. The research findings indicate that this method can effectively classify colonies with high efficiency.<\/jats:p>","DOI":"10.3390\/bioengineering12060625","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T08:22:34Z","timestamp":1749457354000},"page":"625","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Colony Binary Classification Based on Persistent Homology Feature Extraction and Improved EfficientNet"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1194-8203","authenticated-orcid":false,"given":"Zumin","family":"Wang","sequence":"first","affiliation":[{"name":"School of Information Engineering, Dalian University, Dalian 116622, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7701-8060","authenticated-orcid":false,"given":"Ke","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Dalian University, Dalian 116622, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Tang","sequence":"additional","affiliation":[{"name":"Medical College, Dalian University, Dalian 116622, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Dalian University, Dalian 116622, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Dalian University of Technology, Dalian 116024, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3708-6816","authenticated-orcid":false,"given":"Wei","family":"Xu","sequence":"additional","affiliation":[{"name":"Centre for Artificial Intelligence Driven Drug Discovery, Macao Polytechnic University, Macao SAR, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun-Ming","family":"Huang","sequence":"additional","affiliation":[{"name":"Medical College, Dalian University, Dalian 116622, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"175639","DOI":"10.1016\/j.scitotenv.2024.175639","article-title":"Bacterial membrane vesicles from swine farm microbial communities harboring and safeguarding diverse functional genes promoting horizontal gene transfer","volume":"951","author":"Li","year":"2024","journal-title":"Sci. Total Environ."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Carolus, H., Van Dyck, K., and Van Dijck, P. (2019). Candida albicans and Staphylococcus species: A threatening twosome. Front. Microbiol., 10.","DOI":"10.3389\/fmicb.2019.02162"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1974","DOI":"10.1038\/jid.2011.182","article-title":"Microbial symbiosis with the innate immune defense system of the skin","volume":"131","author":"Gallo","year":"2011","journal-title":"J. Investig. Dermatol."},{"key":"ref_4","first-page":"872","article-title":"Candida and candidiasis. American Society for Microbiology Press","volume":"8","author":"Calderone","year":"2011","journal-title":"Emerg. Infect. Dis."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lagudas, M.F.G., and Bureros, K.J.C. (2023). Inhibition of Candida albicans and Staphylococcus epidermidis mixed biofilm formation in a catheter disk model system treated with EtOH\u2013EDTA solution. Lett. Appl. Microbiol., 76.","DOI":"10.1093\/lambio\/ovac074"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1099\/0022-1317-51-4-344","article-title":"Mixed species biofilms of Candida albicans and Staphylococcus epidermidis","volume":"51","author":"Adam","year":"2002","journal-title":"J. Med. Microbiol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bedore, T., Kumar, G., McIntyre, C., Alvarez, A., Leslie, A., Snead, A., and Hudson, A.O. (2024). Genomic analysis of five antibiotic-resistant bacteria isolated from the environment. Microbiol. Resour. Announc., 13.","DOI":"10.1128\/mra.00751-24"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hong, B.Y., Driscoll, M., Gratalo, D., Jarvie, T., and Weinstock, G.M. (2024). Improved DNA extraction and amplification strategy for 16S rRNA gene amplicon-based microbiome studies. Int. J. Mol. Sci., 25.","DOI":"10.3390\/ijms25052966"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhou, X., Liu, X., Liu, M., Liu, W., Xu, J., and Li, Y. (2024). Comparative evaluation of 16S rRNA primer pairs in identifying nitrifying guilds in soils under long-term organic fertilization and water management. Front. Microbiol., 15.","DOI":"10.3389\/fmicb.2024.1424795"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Hopkins, L., Yim, K., Rumora, A., Baykus, M.F., Martinez, L., and Jimenez, L. (2024). Genotypic Identification of Trees Using DNA Barcodes and Microbiome Analysis of Rhizosphere Microbial Communities. Genes, 15.","DOI":"10.3390\/genes15070865"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Xie, Q., Wang, W., Huang, Y., Zheng, M., Shang, S., Jiang, L., Khan, S., and Wu, K. (2024, January 10\u201314). LiteCrypt: Enhancing IoMT Security with Optimized HE and Lightweight Dual-Authorization. Proceedings of the 2024 IEEE 30th International Conference on Parallel and Distributed Systems (ICPADS), Belgrade, Serbia.","DOI":"10.1109\/ICPADS63350.2024.00031"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zieli\u0144ski, B., Plichta, A., Misztal, K., Spurek, P., Brzychczy-W\u0142och, M., and Ocho\u0144ska, D. (2017). Deep learning approach to bacterial colony classification. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0184554"},{"key":"ref_13","first-page":"6105","article-title":"Efficientnet: Rethinking model scaling for convolutional neural networks","volume":"94","author":"Tan","year":"2019","journal-title":"Proc. Int. Conf. Mach. Learn. PMLR"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Samee, N.A., Alhussan, A.A., Ghoneim, V.F., Atteia, G., Alkanhel, R., Al-Antari, M.A., and Kadah, Y.M. (2022). A hybrid deep transfer learning of CNN-based LR-PCA for breast lesion diagnosis via medical breast mammograms. Sensors, 22.","DOI":"10.3390\/s22134938"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"101763","DOI":"10.1016\/j.jksuci.2023.101763","article-title":"ADCGNet: Attention-based dual channel Gabor network towards efficient detection and classification of electrocardiogram images","volume":"35","author":"Arhin","year":"2023","journal-title":"J. King Saud-Univ.-Comput. Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Peng, Y., Wang, H., Sonka, M., and Chen, D.Z. (2024, January 3\u20138). PHG-Net: Persistent Homology Guided Medical Image Classification. Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, USA.","DOI":"10.1109\/WACV57701.2024.00741"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2455","DOI":"10.1021\/acsphotonics.2c00572","article-title":"Deep learning-enabled detection and classification of bacterial colonies using a thin-film transistor (TFT) image sensor","volume":"9","author":"Li","year":"2022","journal-title":"ACS Photonics"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Balmages, I., Liepins, J., Zolins, S., Bliznuks, D., Broks, R., Lihacova, I., and Lihachev, A. (2023). Tools for classification of growing\/non-growing bacterial colonies using laser speckle imaging. Front. Microbiol., 14.","DOI":"10.3389\/fmicb.2023.1279667"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1007\/s10559-023-00569-z","article-title":"Classification of Pathologies on Medical Images Using the Algorithm of Random Forest of Optimal-Complexity Trees","volume":"59","author":"Babenko","year":"2023","journal-title":"Cybern. Syst. Anal."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Periyasamy, S., Prakasarao, A., Menaka, M., Venkatraman, B., and Jayashree, M. (2022). Support vector machine based methodology for classification of thermal images pertaining to breast cancer. J. Therm. Biol., 110.","DOI":"10.1016\/j.jtherbio.2022.103337"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Huang, H., Wang, C., Zhao, L., Wang, W., Ding, S., and Vasilakos, A. (2025). Wi-Fi Sensing Based on Deep Supervised Dictionary Learning for Robust Device-Free Localization. IEEE Trans. Veh. Technol., 1\u201311.","DOI":"10.1109\/TVT.2025.3552082"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"02031","DOI":"10.1051\/e3sconf\/202346502031","article-title":"Monkeypox Classification based on Skin Images using CNN: EfficientNet-B0","volume":"Volume 465","author":"Taruno","year":"2023","journal-title":"Proceedings of the E3S Web of Conferences"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Chen, Y., Lin, Y., Xu, X., Ding, J., Li, C., Zeng, Y., Liu, W., Xie, W., and Huang, J. (2022). Classification of lungs infected COVID-19 images based on inception-ResNet. Comput. Methods Programs Biomed., 225.","DOI":"10.1016\/j.cmpb.2022.107053"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Sun, J., Wu, B., Zhao, T., Gao, L., Xie, K., Lin, T., Sui, J., Li, X., Wu, X., and Ni, X. (2023). Classification for thyroid nodule using ViT with contrastive learning in ultrasound images. Comput. Biol. Med., 152.","DOI":"10.1016\/j.compbiomed.2022.106444"},{"key":"ref_25","first-page":"5967","article-title":"CE-EEN-B0: Contour Extraction Based Extended EfficientNet-B0 for Brain Tumor Classification Using MRI Images","volume":"74","author":"Mahesh","year":"2023","journal-title":"Comput. Mater. Contin."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ar\u00e9valo-Jaimes, B.V., Admella, J., Blanco-Cabra, N., and Torrents, E. (2023). Culture media influences Candida parapsilosis growth, susceptibility, and virulence. Front. Cell. Infect. Microbiol., 13.","DOI":"10.3389\/fcimb.2023.1323619"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Ni, H., Shi, Z., Karungaru, S., Lv, S., Li, X., Wang, X., and Zhang, J. (2023). Classification of typical pests and diseases of Rice based on the ECA attention mechanism. Agriculture, 13.","DOI":"10.3390\/agriculture13051066"},{"key":"ref_28","first-page":"2202331","article-title":"Topological data analysis and machine learning","volume":"8","author":"Leykam","year":"2023","journal-title":"Adv. Phys. X"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1080\/13658816.2022.2155654","article-title":"Topological data analysis for geographical information science using persistent homology","volume":"37","author":"Corcoran","year":"2023","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Jazayeri, N., Jazayeri, F., and Sajedi, H. (2022, January 3\u20135). Medical Image Segmentation for Skin Lesion Detection via Topological Data Analysis. Proceedings of the IEEE: 2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM), Seoul, Republic of Korea.","DOI":"10.1109\/IMCOM53663.2022.9721758"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hu, C.S., Lawson, A., Chen, J.S., Chung, Y.M., Smyth, C., and Yang, S.M. (2021). Toporesnet: A hybrid deep learning architecture and its application to skin lesion classification. Mathematics, 9.","DOI":"10.3390\/math9222924"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1007\/s40840-024-01663-x","article-title":"Lower bounds on the homology of Vietoris\u2013Rips complexes of hypercube graphs","volume":"47","author":"Adams","year":"2024","journal-title":"Bull. Malays. Math. Sci. Soc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"034319","DOI":"10.1103\/PhysRevE.106.034319","article-title":"Weighted simplicial complexes and their representation power of higher-order network data and topology","volume":"106","author":"Baccini","year":"2022","journal-title":"Phys. Rev. E"},{"key":"ref_34","unstructured":"Chen, X., Cai, Y., Wu, Y., Xiong, B., and Park, T. (2024). Multi-Scale Semantic Segmentation with Modified MBConv Blocks. arXiv."},{"key":"ref_35","first-page":"1","article-title":"Klasifikasi Jenis Tumor Otak Menggunakan Arsitekture Mobilenet V2","volume":"13","author":"Winnarto","year":"2022","journal-title":"J. Simetris"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"6037","DOI":"10.1007\/s10462-022-10148-x","article-title":"Attention, please! A survey of neural attention models in deep learning","volume":"55","author":"Colombini","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Liu, H., Liu, F., Fan, X., and Huang, D. (2021). Polarized self-attention: Towards high-quality pixel-wise regression. arXiv.","DOI":"10.1016\/j.neucom.2022.07.054"},{"key":"ref_38","first-page":"4023","article-title":"ECAENet: EfficientNet with efficient channel attention for plant species recognition","volume":"43","author":"Guang","year":"2022","journal-title":"J. Intell. Fuzzy Syst."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Chicco, D., and Jurman, G. (2023). The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. Biodata Min., 16.","DOI":"10.1186\/s13040-023-00322-4"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11633-022-1411-7","article-title":"A survey of synthetic data augmentation methods in machine vision","volume":"21","author":"Mumuni","year":"2024","journal-title":"Mach. Intell. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1109\/ACCESS.2023.3347922","article-title":"Finger Vein Recognition Based on ResNet With Self-Attention","volume":"12","author":"Zhang","year":"2024","journal-title":"IEEE Access"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1142","DOI":"10.1109\/TIFS.2023.3328431","article-title":"ResNeXt+: Attention mechanisms based on ResNeXt for malware detection and classification","volume":"19","author":"He","year":"2023","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.jri.2009.06.183","article-title":"TLR2 ligation by Listeria moncytogenes and its effects on the cytokine profile of trophoblast cells","volume":"2","author":"Scholz","year":"2009","journal-title":"J. Reprod. Immunol."},{"key":"ref_44","first-page":"100628","article-title":"Breast ultrasound image classification and physiological assessment based on GoogLeNet","volume":"16","author":"Chen","year":"2023","journal-title":"J. Radiat. Res. Appl. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1007\/s42452-024-06048-0","article-title":"Thoracic computed tomography (CT) image-based identification and severity classification of COVID-19 cases using vision transformer (ViT)","volume":"6","author":"Taye","year":"2024","journal-title":"Discov. Appl. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"44141","DOI":"10.1007\/s11042-022-13235-x","article-title":"Hyperspectral imaging and target detection algorithms: A review","volume":"81","author":"Sneha","year":"2022","journal-title":"Multimed. Tools Appl."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/6\/625\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:48:42Z","timestamp":1760032122000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/6\/625"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,9]]},"references-count":46,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["bioengineering12060625"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering12060625","relation":{},"ISSN":["2306-5354"],"issn-type":[{"type":"electronic","value":"2306-5354"}],"subject":[],"published":{"date-parts":[[2025,6,9]]}}}