Analysis of infected blood cell images using morphological operators

By C. D. Ruberto, Andrew G. Dempster, Shahid Khan, B. Jarra. Image and Vision Computing, 2002

321 citations recorded by the source corpus.

Subfields: Biophysics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/4fea65c6b0ad0630610d773ebd0dbf810b1bf249

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biophysics

1. Stefan Jaeger
2. George R. Thoma
3. Mahdieh Poostchi
4. Richard James Maude
5. Kamolrat Silamut

In Computer Vision and Pattern Recognition

1. David M. Rubin
2. Stefan Jaeger
3. George R. Thoma
4. Mahdieh Poostchi
5. Adriano G. Dusé
6. Nicholas E. Ross
7. Richard James Maude
8. Kamolrat Silamut

Citations in the corpus

• Image analysis and machine learning for detecting malaria (2018, background): “[80] Di Ruberto C, Dempster A, Khan S, Jarra B.”
• Automated image processing method for the diagnosis and classification of malaria on thin blood smears (2006, methodology): “blood slides [3] is used as a starting point for the algorithm, from which many of the pre-processing and image segmentation steps are derived.”
• An automatic segmentation algorithm for 3D cell cluster splitting using volumetric confocal images (2011, background): “…et al ., 1995; Najman & Schmitt, 1996; Malpica et al ., 1997; Wang, 1998; Solorzano etal .,1999;Adiga&Chaudhuri,2001;Kumar etal ., 2002, 2006; Ruberto et al ., 2002; Lin et al ., 2003; W¨ahlby et al ., 2003; W¨ahlby et al ., 2004; Nilsson & Heyden, 2005; Gniadek & Warren, 2007; Li et al.,…”