# Staining-Independent Malaria Parasite Detection and Life Stage Classification in Blood Smear Images
## 4 Experimental Results  
The performance of malaria parasite detection and life stage classification are evaluated separately and shown in this section. As mentioned in Section 3.2, to solve the unbalanced data problem, the number of each infected cell class was increased to the same level as that of red blood cells via image augmentation. The numbers of images in each class before and after image augmentation are shown in Table 1. Tables 2 and 3 illustrate \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Dataset**} & \multirow{2}{*}{**Classes of Cells/Infected Cells**} & **Original Number of Images** & **Number of Images** \\  & & **(before Augmentation)** & **after Augmentation** \\ \hline \multirow{6}{*}{MBB (_P. vivax_)} & Red blood cell & 83,034 & 83,034 \\  & Ring & 522 & 82,095 \\  & Trophozoite & 1584 & 80,762 \\  & Schizont & 190 & 79,401 \\  & Gametocyte & 156 & 80,257 \\ \hline \multirow{6}{*}{MP-IDB (_P. vivax_)} & Red blood cell & 2857 & 2857 \\  & Ring & 37 & 2842 \\  & Trophozoite & 5 & 2782 \\  & Schizont & 11 & 2804 \\  & Gametocyte & 8 & 2819 \\ \hline \multirow{6}{*}{MP-IDB (_P. oval_)} & Red blood cell & 2606 & 2606 \\  & Ring & 12 & 2633 \\  & Trophozoite & 12 & 2623 \\  & Schizont & 1 & 2322 \\  & Gametocyte & 7 & 2605 \\ \hline \multirow{6}{*}{MP-IDB (_P. falciparum_)} & Red blood cell & 2407 & 2407 \\  & Ring & 1 & 2395 \\ \cline{1-1}  & Trophozoite & 23 & 2339 \\ \cline{1-1}  & Schizont & 10 & 2315 \\ \cline{1-1}  & Gametocyte & 7 & 2306 \\ \hline \multirow{6}{*}{MP-IDB (_P. falciparum_)} & Red blood cell & 9589 & 9589 \\ \cline{1-1}  & Ring & 1022 & 9196 \\ \cline{1-1}  & Trophozoite & 42 & 9474 \\ \cline{1-1}  & Schizont & 17 & 9335 \\ \cline{1-1}  & Gametocyte & 7 & 9070 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Number of images in each class before and after image augmentation. the malaria parasite detection performance, including the precision, recall, F1-score, and accuracy for 2 approaches: (1) preprocessing each input color image in the color space and then converting each output into a grayscale image, and (2) converting each input color image into the grayscale space and then preprocessing the corresponding grayscale image, respectively. The sample output images of 5 different image preprocessing methods using the 2 approaches are illustrated in Figures 4 and 5, respectively. Table 4 shows malaria parasite detection performance on the MP-IDB dataset by using the best training model from the MBB dataset. For malaria parasite life stage classification, the sample cropped single cell images using 3 cropping methods, i.e., direct cropping, zero padding, and cell cropping with background, are shown in Figure 6. The malaria parasite life stage classification results on the MBB test sets using 3 different cell cropping methods are shown in Table 5. The corresponding life stage classification results on the MP-IDB test sets for 4 different species of malaria parasites, i.e., _P. vivax, P. ovale, P. malariae_, and _P. falciparum_, are shown in Tables 6-9, respectively. It is worthwhile noting that, for each species, a 5-class classification problem is considered for red blood cells and 4 distinct stages of life of malaria parasites, i.e., ring, trophozoite, schizont, and gametocyte.