The dental plaque disclosing agent helps guide plaque removal by revealing plaque on the teeth. However, existing toothbrushes cannot provide visualization of the stained plaque beneath the toothpaste foam during brushing. To fill this gap, this paper proposes PIT and uses smartphone to provide real-time plaque visualization during brushing. PIT introduces novel hardware, including a micro camera, four green LEDs, and a mechanical structure, offering a stable camera view of bristle position and bristle rotation. To address the challenge of toothpaste foam obstruction, we derived an optical channel model that guided the design of the light source to enhance plaque visibility. Furthermore, we designed a deep neural network specifically for plaque segmentation under thick foam. Finally, the trained distilled student model was run on a smartphone and evaluated on both denture models and human subjects. The results show that PIT achieved an IoU (Intersection over Union) of 75.22% and a latency of 29 ms, with robust performance across various conditions. Evaluation by 10 participants revealed that PIT helped reduce plaque coverage to 5.6% within two minutes of brushing, significantly outperforming existing advanced toothbrushes.