Disease is the conspicuous wellspring of mortality in around the world. The malignant growth which is cancer arises because of unrestrained varieties in a cell. Stringent diagnosis of cancer with explicit procedure is a prerequisite for retaining human lives. The relevant image transforms such as STFT and WT utilize a detection system where the cancerous image features are retained and localize the signal characteristics in different domains. The predetection of malignant growth prompts proper conclusion to either control or fix disease, as at later stages the patient may not react to the treatment. The suspicious tissues are examined and diagnosed with the help of MRI. These filtered pictures can be used to evaluate the destructive cells. The TFD yields appropriate information in the study of non-stationary images. The key objective of TFD representation is to figure out the variations in the frequency substance of images with respect to time. The TFD representation is proposed by STFT and WT to analyze, evaluate and transform the time differing category of images. © 2021, Springer Nature Singapore Pte Ltd.