Cancer has been an enormous issue for a long time. The ability to precisely localize cancer at an early stage, crucial for effective treatment, has been made possible by recent developments in molecular imaging, which have radically altered cancer research. Molecular imaging non-invasiveness, speed, safety, and user-friendliness make it a priceless asset in the fight against cancer in its early stages. Imaging technologies including positron emission tomography (PET), magnetic resonance imaging (MRI), and computed tomography (CT) enable the early diagnosis of tiny or hidden malignancies by offering high-resolution, real-time molecular visualization of tumors. Clinicians can detect tumors before they become noticeable or cause symptoms, which allows for better treatment results and early intervention. When it comes to cancer detection and therapy, molecular imaging is crucial. Modern molecular imaging techniques allow for a more exact visualization of malignant cells and tissues; they include fluorescence imaging, MRI, PET, and CT. The advancements in cancer diagnosis, treatment response monitoring in real-time, and our overall knowledge of cancer biology have opened up exciting new possibilities for targeted treatment and early intervention. Artificial intelligence (AI) and machine learning (ML) are transforming molecular imaging by making data interpretation, pattern recognition, and picture analysis much better. These advancements in technology pave the way for more precise anomaly identification, better tumor segmentation, and individualized treatment strategies. Imaging techniques may be optimized by AI-driven algorithms, which speed up cancer diagnostics while decreasing the likelihood of a human mistake. This chapter provides a comprehensive discussion of various molecular imaging modalities for early-stage cancer detection. In addition, we incorporated our discussion with AI and machine learning concepts for imaging modalities.